Methods for evaluating tumor cell spheroids using 3D microfluidic cell culture device

ABSTRACT

Provided herein are methods for evaluating tumor cell spheroids in a three-dimensional microfluidic device by determining changes in the relative levels of live cells and dead cells in aliquots cultured under different conditions. Methods described herein allow ex vivo recapitulation of the tumor microenvironment such that the in vivo effectiveness of a test compound in treating tumor tissue may be predicted.

RELATED APPLICATIONS

This application is a continuation-in-part of International Application No. PCT/US2018/025390, filed Mar. 30, 2018, and entitled “METHODS FOR EVALUATING TUMOR CELL SPHEROIDS USING 3D MICROFLUIDIC CELL CULTURE DEVICE,” which claims the benefit of U.S. provisional application No. 62/480,192, filed on Mar. 31, 2017, the entire contents of which is incorporated by reference herein.

FEDERALLY SPONSORED RESEARCH

This invention was made with government support under K08 CA138918-01A1 and R01 CA190394-01 awarded by the National Institutes of Health. The government has certain rights in the invention.

BACKGROUND

Existing patient-derived cancer models, including circulating tumor cells (CTCs), organoid cultures, and patient-derived xenografts (PDXs) can guide precision cancer therapy, but take weeks to months to generate and lack the native tumor immune microenvironment. Current approaches to study anti-tumor immune responses in patients are also limited by remote measurements in whole blood or plasma, or static assessment of biopsies.

Recently there has been developed a 3D microfluidic device for the short-term culture of murine- and patient-derived organotypic tumor spheroids. Cultured tumor spheroids are believed by some to more closely resemble the native immune microenvirolunent.

It would be desirable to be able to assess the effects of single drugs and combinations of drugs on tumor cells in the tumor micro-environment. It would be particularly helpful if there were a way to evaluate simultaneously the effects of a combination of immune blockade and anticancer compounds ex vivo. To date, efforts to evaluate tumor cells have been confounded by (i) the tumor cells changing when removed from the body, (ii) the absence of an intact immune system communicating with the tumor microenvironment when the tumor cells are removed from the body, (iii) the inability to distinguish the effects of tumor removal and culturing from the effects of a drug applied in vitro, and (iv) the complexity of measuring at a molecular level immune based markers and other markers which might predict whether a drug might work in vivo based on experiments conducted in vitro. To date, there is no simple assay for evaluating in in a high throughput manner the effects of drugs on human cancer cells in a native tumor microenvironment.

SUMMARY

It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid contains sufficient immune components to be predictive of a drug's activity when administered in vivo. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid contains sufficient immune components such that combinations of immune blockade compounds and anti-cancer drugs can be assessed, the results being predictive of administering the drugs in vivo. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid can be evaluated optically and reproducibly, to establish the effects of drugs on the tumor cells within the spheroids, while distinguishing the effects on tumor cells resulting from the act of culturing the tumor cells. It has been discovered, surprisingly, that such techniques for evaluating tumor spheroids can be utilized in a high throughput method for determining the relative amounts of live and dead cells in an environment mimicking that occurring in vivo.

In one aspect, the invention involves a novel approach for evaluating ex vivo response to Immune Checkpoint Blockade (ICB) using murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS) cultured in a 3-dimensional microfluidic system. Spheroids isolated from fresh mouse and human tumor samples retain autologous lymphoid and myeloid cell populations, including antigen-experienced tumor infiltrating CD4 and CD8 T lymphocytes, and respond to ICB in short-term ex vivo culture. Tumor killing was recapitulated ex vivo using MDOTS derived from the anti-PD-1 sensitive MC38 syngeneic mouse cancer model, whereas relative resistance to anti-PD-1 therapy was preserved in the CT26 and B16F10 syngeneic models. Systematic cytokine/chemokine profiling following PD-1 blockade in PDOTS from patients with melanoma and other tumors identified significant induction of the immunoattractants CCL19 and CXCL13, which was confirmed in vivo and correlated with evidence of intratumoral immune cell infiltration. Resistance to anti-PD1 treatment in MDOTS and PDOTS also tracked with coinduction of immune suppressive chemokines. Ex vivo profiling revealed a combination therapy as a novel therapeutic strategy to enhance sensitivity to PD-1 blockade in this setting, which effectively predicted tumor response in vivo. These findings demonstrate feasibility of ex vivo profiling of PD-1 blockade, and offer a novel functional approach to facilitate precision immunooncology and develop novel therapeutic combinations.

According to one aspect of the invention, a method for evaluating tumor cell spheroids in a three-dimensional microfluidic device is provided. The method involves:

obtaining tumor spheroids from an enzyme treated tumor sample, suspending a first aliquot of the tumor spheroids in biocompatible gel; suspending a second aliquot of the tumor spheroids in biocompatible gel;

placing the first aliquot of the tumor spheroids in biocompatible gel in a first three-dimensional device,

contacting the first aliquot with a first fluorophore dye selective for dead cells, the first fluorophore dye emitting fluorescence at a first wavelength when bound to a dead cell,

contacting the first aliquot with a second fluorophore dye selective for live cells, the second fluorophore dye emitting fluorescence at a second wavelength different from the first wavelength when bound to a live cell,

measuring total fluorescence emitted by each of the first and second fluorophore dyes in the first aliquot,

culturing the second aliquot in a second three-dimensional device,

contacting the second aliquot with the first fluorophore dye,

contacting the second aliquot with the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye,

measuring total fluorescence emitted by each of the first and second fluorophore dyes in the second aliquot,

wherein an increase or decrease in the ratio of live cells to dead cells in each of the aliquots may be assessed.

In one embodiment, the total fluorescence emitted by each of the first and second fluorophore dyes is measured using a camera, preferably at a resolution of at least 2×, at least 3×, at least 4× or more, from directly above or below each three-dimensional device, and preferably wherein the three-dimensional devices are placed on a moveable stage permitting the camera to capture the total fluorescence in each aliquot.

In some embodiments, the dead cell fluorescence and the live cell fluorescence can be added together to yield a live and dead cell total. The amount of dead cells may be expressed as a percentage of the dead cell fluorescence to the total fluorescence. The amount of live cells can be expressed as a percentage of the live cell fluorescence to the total. In some embodiments, the dead cell fluorescence and the live cell fluorescence can be expressed as a ratio, that is, dead cells/live cells or live cells/dead cells. In this manner, changes to the number of dead cells to live cells can be tracked over time, wherein an initial ratio is established prior to culturing and changes to the ratio are determined over time.

In some embodiments, there are multiple aliquots of tumor spheroids, for example three, or four, or five, or six or more than six, and the contacting of the third, fourth, fifth, sixth or more than sixth such aliquots with the first fluorophore dye and second fluorophore dye is carried out, for example, two days, three days, four days, five days, and more than five days, respectively, after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye. The timing of testing aliquots may be separated by any time period, such as one day, less than a day, two days or three or more days. In one embodiment, an aliquot is tested six days after placing the spheroids in the gel.

In any of the embodiments, the second (or any subsequent) aliquot is contacted with at least one test compound during the culturing of the second aliquot and wherein said culturing of the second aliquot in the presence of the test compound occurs for at least 24 hours, at least two days, at least three days, at least four days, at least five days, or at least 6 days or more.

In any of the foregoing embodiments, the second aliquot can be contacted with at least two test compounds during the culturing of the second aliquot and wherein said culturing of the second aliquot in the presence of the test compounds occurs for at least 24 hours, at least two days, at least three days, at least four days, at least five days, or at least 6 days, and preferably wherein at least one of the test compounds is an immune checkpoint inhibitor.

The number of spheroids can be any number of spheroids convenient and available to the researcher, but in the system described below, the number of spheroids in the first and the second aliquots each contain between about 15 and 30 spheroids, preferably between about 20 and 25 spheroids.

In some embodiments, the first three-dimensional device can be a first three-dimensional microfluidic device and the second three-dimensional device can be a second three-dimensional microfluidic device. In some embodiments, the culturing of the first aliquot in the first three-dimensional microfluidic device, is for less than 6 hours, less than 3 hours, less than 2 hours and even less than 1 hour prior to contacting the first aliquot with the first and second fluorophore dyes. In particular, it may be desirable to contact the first aliquot with the dyes prior to culturing the spheroids at all, that is essentially upon introducing the spheroids into the three dimensional device.

In any of the foregoing embodiments, the enzyme can be collagenase.

In any of the foregoing embodiments, the first fluorophore dye can be propidium iodide, DRAQ7, 7-AAD, eBioscience Fixable Viability Dye EFLUOR® 455UV, eBioscience Fixable Viability Dye EFLUOR® 450, eBioscience Fixable Viability Dye EFLUOR® 506, eBioscience Fixable Viability Dye EFLUOR® 520, eBioscience Fixable Viability Dye EFLUOR® 660, eBioscience Fixable Viability Dye EFLUOR® 780, BioLegend Zombie AQUA™, BioLegend Zombie NIR™, BioLegend Zombie RED™ BioLegend Zombie VIOLET™, BioLegend Zombie UV™, or BioLegend Zombie YELLOW™, and/or the second fluorophore dye can be acridine orange, nuclear green LCS1 (ab138904), DRAQ5 (ab108410), CyTRAK Orange, NUCLEAR-ID Red DNA stain (ENZ-52406), SiR700-DNA, calcein AM, calcein violet AM, calcein blue AM, VYBRANT® DYECYCLE™ Violet, VYBRANT® DYECYCLE™ Green, VYBRANT® DYECYCLE™ Orange, or VYBRANT® DYECYCLE™ Ruby.

In any of the foregoing embodiments, the tumor spheroids can be obtained by mincing a primary tumor sample in a medium supplemented with serum; treating the minced primary tumor sample with an enzyme; and harvesting tumor spheroids from the enzyme treated sample. In some embodiments, the minced primary tumor sample is treated with the enzyme in an amount and/or for a time sufficient to yield a partial digestion of the minced primary tumor sample, and preferably wherein the treatment is for between 10 minutes and 60 minutes, and more preferably between 15 minutes and 45 minutes at a temperature of 25° C. to 39° C.

In any of the foregoing embodiments, the biocompatible gel can be collagen, BD Matrigel™ Matrix Basement Membrane, or fibrin hydrogel.

In any of the foregoing embodiments, the tumor sample can be derived from a murine model. In some embodiments, the murine model is a syngeneic model selected from the group consisting of Bladder MBT-2, Breast 4T1, EMT6, Colon, Colon26, CT-26, MC38, Fibrosarcoma WEHI-164, Kidney Renca, Leukemia C1498, L1210, Liver H22, KLN205, LL/2, LewisLung, Lymphoma A20 S, E.G7-OVA, EL4, Mastocytoma P815, Melanoma B16-BL6, B16-F10, S91, Myeloma MPC-11, Neuroblastoma Neuro-2a, Ovarian: ID8, Pancreatic Pan02, Plasmacytoma J558, and Prostate RM-1.

In any of the foregoing embodiments, the tumor sample can be a human tumor sample.

In any of the foregoing embodiments, the tumor sample can be a patient derived xenograft (PDX).

In any of the foregoing embodiments, the three-dimensional device can include one or more fluid channels flanked by one or more gel cage regions, wherein the one or more gel cage regions comprises the biocompatible gel in which the tumor spheroids are embedded, and wherein the device recapitulates in vivo tumor microenvironment. In any of the foregoing embodiments, the three-dimensional device can include: a substrate comprised of an optically transparent material and further comprising i) one or more fluid channels; ii) one or more fluid channel inlets; iii) one or more fluid channel outlets; iv) one or more gel cage regions; and v) a plurality of posts; wherein all or a portion of each gel cage region is flanked by all or a portion of one or more fluid channels, thereby creating one or more gel cage region-fluid channel interface regions; each gel cage region comprises at least one row of posts which forms the gel cage region; and the one or more gel cage region has a height of less than 500 μm.

In any of the foregoing embodiments, the test compound can be a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof. In any of the foregoing embodiments, the first test compound can be a chemotherapeutic compound, an immunomodulatory compound, or radiation. In any of the foregoing embodiments, the first test compound can be an alkylating compound, an antimetabolite, an anthracycline, a proteasome inhibitor, or an mTOR inhibitor. In any of the foregoing embodiments, the first test compound can be an immune modulator.

In some embodiments, the method further comprises isolating RNA from the first aliquot and second aliquot of tumor spheroids; and analyzing gene expression of the first aliquot and second aliquot of tumor spheroids based on the isolated RNA, wherein the gene expression is analyzed by performing RNA sequencing (RNA-seq) on the isolated RNA

In another aspect, provided herein is a method for detecting a change in tumor cell spheroids upon exposure to a test compound. The method comprises:

culturing a first aliquot of tumor cell spheroids in a first three-dimensional device;

culturing a second aliquot of tumor cell spheroids in the presence of a first test compound in a second three-dimensional device; and

detecting a change in the second aliquot as compared to the first aliquot, wherein the change is selected from:

a clustering of immune cells around one or more of the tumor cell spheroids of the first or second aliquot;

a decrease in size and/or number of the tumor cell spheroids of the first or second aliquot; or

a chemical change.

In some embodiments, the second aliquot is cultured in the presence of the first test compound and a second test compound. In some embodiments, the first aliquot is cultured in the presence of the first test compound.

In some embodiments, the method further comprises:

culturing a third aliquot of tumor cell spheroids in the presence of the first test compound and the second test compound in a third three-dimensional device; and

detecting a change in the third aliquot relative to the first and/or second aliquot.

In some embodiments, the first aliquot is cultured in the presence of the second and/or a third test compound. In some embodiments, the second aliquot is cultured in the presence of the third and/or a fourth test compound. In some embodiments, the third aliquot is cultured in the presence of the third and/or fourth test compound.

In some embodiments, detecting a chemical change comprises detecting a presence of a biological molecule secreted into tumor cell spheroid cell culture supernatant of the first, second, and/or third aliquots.

In some embodiments, the biological molecule is a protein, a carbohydrate, a lipid, a nucleic acid, a metabolite, or a combination thereof. In some embodiments, the biological molecule is a chemokine or a cytokine. In some embodiments, the biological molecule is known to be associated with activation of the immune system or otherwise an enhancement of the immune response.

In some embodiments, detecting a chemical change comprises detecting a change in nucleic acid content. In some embodiments, detecting the change in nucleic acid content comprises detecting a change in extracellular nucleic acids. In some embodiments, detecting the change in nucleic acid content comprises detecting a change in nucleic acids isolated from tumor cell spheroids from the first, second, and/or third aliquots.

In some embodiments, detecting the change in nucleic acid content comprises detecting a change in gene expression. In some embodiments, detecting a change in gene expression comprises detecting a change expression of genes associated with cytotoxicity. In some embodiments, genes associated with cytotoxicity comprise cytokines and cytokine receptors.

In some embodiments, detecting the change in nucleic acid content comprises analyzing DNA and/or RNA from the first, second, and/or third aliquots of tumor cell spheroids. In some embodiments, RNA from the first, second, and/or third aliquots of tumor cell spheroids is analyzed by RNA sequencing.

In some embodiments, the first, second, third, and/or fourth test compound is a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof. In some embodiments, the first, second, third, and/or fourth test compound is an immune modulator. In some embodiments, the immune modulator comprises immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of CTLA-4, PD-1, PD-L1, TIM3, LAG3, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GAL9, A2aR, and VISTA. In some embodiments, the immune checkpoint inhibitor inhibits PD1. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second test compound is a small molecule compound. In some embodiments, the small molecule compound is a TBK-1 inhibitor. In some embodiments, the first, second, third, and/or fourth test compound is a chemical from a test compound library. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second, third, and/or fourth test compound is a chemical from a test compound library.

In some embodiments, the first, second, and/or third aliquots are cultured in a biocompatible gel. In some embodiments, the first, second, and/or third aliquots are suspended in a biocompatible gel in a fluid channel of the three-dimensional microfluidic device before culturing.

In some embodiments, the first, second, and/or third aliquots are obtained from an enzyme treated tumor sample.

In another aspect, provided herein is a method for evaluating tumor cell spheroids in a three-dimensional microfluidic device. The method comprises:

culturing a first aliquot of tumor spheroids in a first three-dimensional device,

culturing the second aliquot of tumor spheroids in a second three-dimensional device in the presence of a first test compound;

isolating RNA from the first aliquot and second aliquot of tumor spheroids; and

analyzing gene expression of the first aliquot and second aliquot of tumor spheroids based on the isolated RNA.

In some embodiments, the second aliquot is cultured in the presence of a first test compound and a second test compound.

In some embodiments, the method further comprises:

culturing the third aliquot of tumor spheroids in a third three-dimensional device in the presence of the first test compound and a second test compound;

isolating RNA from the third aliquot of tumor spheroids; and

analyzing gene expression of the third aliquot of tumor spheroids based on the isolated RNA.

In some embodiments, the second aliquot is cultured in the presence of a third and/or fourth test compound. In some embodiments, the third aliquot is cultured in the presence of a third and/or fourth test compound.

In some embodiments, the RNA is isolated from the supernatant or from the cell culture of the first aliquot and second aliquot of tumor spheroids.

In some embodiments, the gene expression of the first aliquot and second aliquot of tumor spheroids is analyzed by performing RNA sequencing (RNA-seq) on the isolated RNA.

In some embodiments, the tumor cell spheroids are obtained from an enzyme treated tumor sample.

In some embodiments, the first, second, third, and/or fourth test compound is a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof. In some embodiments, the first test compound is an immune modulator. In some embodiments, the immune modulator comprises immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of CTLA-4, PD-1, PD-L1, TIM3, LAG3, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GAL9, A2aR, and VISTA. In some embodiments, the immune checkpoint inhibitor inhibits PD1. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second test compound is a small molecule compound. In some embodiments, the small molecule compound is a TBK-1 inhibitor. In some embodiments, the first, second, third, and/or fourth test compound is a chemical from a test compound library. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second, third, and/or fourth test compound is a chemical from a test compound library.

In some embodiments, the first, second, and/or third aliquots are cultured in a biocompatible gel. In some embodiments, In some embodiments, the first, second, and/or third aliquots are suspended in a biocompatible gel in a fluid channel of the three-dimensional microfluidic device before culturing.

BRIEF DESCRIPTION OF THE DRAWINGS

The skilled artisan will understand that the figures, described herein, are for illustration purposes only. It is to be understood that, in some instances, various aspects of the invention may be shown exaggerated or enlarged to facilitate an understanding of the invention. In the drawings, like reference characters generally refer to like features, functionally similar and/or structurally similar elements throughout the various figures. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the teachings. The drawings are not intended to limit the scope of the present teachings in any way.

The features and advantages of the present invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings.

When describing embodiments in reference to the drawings, direction references (“above,” “below,” “top,” “bottom,” “left,” “right,” “horizontal,” “vertical,” etc.) may be used. Such references are intended merely as an aid to the reader viewing the drawings in a normal orientation. These directional references are not intended to describe a preferred or only orientation of an embodied device. A device may be embodied in other orientations.

As is apparent from the detailed description, the examples depicted in the figures and further described for the purpose of illustration throughout the application describe non-limiting embodiments, and in some cases may simplify certain processes or omit features or steps for the purpose of clearer illustration.

FIG. 1A is a schematic for preparation and analysis of MDOTS/PDOTS (S2 fraction) from murine or patient-derived tumor specimens.

FIG. 1B depicts MC38 allograft immune profiling by flow cytometry comparing bulk tumor (n=5) to S1, S2, S3 (n=6) spheroid fractions (Kruskal-Wallis with Dunn's multiple comparisons test, α=0.05; ns=not significant).

FIG. 1C depicts immune profiling of PDOTS (S2; n=40) (upper panel=% live cells, lower panel=% CD45+ cells) with indicated patient/tumor characteristics, grouped by tumor type and ranked by % CD8+ T cells.

FIG. 1D depicts immune cell correlation of S2/S3 fractions (CD45, n=14; CD3, n=15; CD4/CD8, n=13; CD4+CD45RO+, n=9; CD8+CD45RO+, n=8; activated=CD38+ and/or CD69+, n=6), R2 significant for all comparisons.

FIG. 1E depicts PD-1, CTLA-4, TIM-3 expression on CD4 and CD8 T cell populations in S2/S3 fractions (n=6), R2 significant for all comparisons.

FIG. 2A depicts phase-contrast imaging (4×) of MC38 MDOTS in 3D microfluidic culture.

FIG. 2B is a cytokine heatmap from cultured MC38 MDOTS expressed as log-2 fold change relative to Day 1.

FIG. 2C is a cytokine heatmap from cultured B16F10 MDOTS expressed as log-2 fold change relative to Day 1.

FIG. 2D illustrates MC38 allograft tumor volume following isotype control IgG (n=10) or rat-anti-mouse anti-PD-1 antibody (n=10) treatment.

FIG. 2E illustrates Day 22 MC38 tumor volumes (unpaired 2-sided t-test, p<0.05).

FIG. 2F is a schematic of MDOTS Live/Dead Imaging workflow.

FIG. 2G illustrates Live (AO=green)/dead (PI=red) quantification of MC38 MDOTS Day 0 (immediately after loading), Day 3, and Day 6 following IgG control or indicated anti-PD-1 antibody doses; n=4, biological replicates, **p<0.01, ****p<0.0001, Kruskal-Wallis Dunnett's with multiple comparisons test).

FIG. 2H illustrates Live/dead analysis of MC38 spheroids lacking immune cells±anti-PD 1 (n=4, biological replicates).

FIG. 2I illustrates Live/dead analysis of CT26 MDOTS±anti-PD1 (n=3, biological replicates, ****p<0.0001).

FIG. 2J illustrates Live/dead analysis of B16F10 MDOTS±anti-PD1 (n=3, biological replicates).

FIG. 2K depicts deconvolution fluorescence microscopy of MC38 and B16F10 MDOTS Day 6±anti-PD1 (representative images shown).

FIG. 3A is a cytokine heatmap that illustrates day 3±anti-PD-1 (n=28) expressed as log 2 fold-change (L2FC) relative to untreated control.

FIG. 3B is a cytokine heatmap that illustrates day 3±anti-CTLA-4 (n=24) expressed as log 2 fold-change (L2FC) relative to untreated control.

FIG. 3C is a cytokine heatmap that illustrates day 3±anti-PD-1±anti-CTLA-4 (n=24) expressed as log 2 fold-change (L2FC) relative to untreated control.

FIG. 3D depicts absolute CCL19/CXCL13 levels following single checkpoint blockade (2-sided, paired, t-test, α=0.05).

FIG. 3E depicts absolute CCL19/CXCL13 levels following single checkpoint blockade (2-sided, paired, t-test, α=0.05).

FIG. 3F depicts absolute CCL19/CXCL13 levels following dual checkpoint blockade (2-sided, paired, t-test, α=0.05).

FIG. 3G is a heatmap that illustrates CCL19/CXCL13 mRNA levels from melanoma biopsy samples on anti-PD1 treatment relative to pre-PD-1 (L2FC) by qRT-PCR (n=12).

FIG. 3H is a heatmap that illustrates CCL19/CXCL13 mRNA levels from melanoma biopsy samples on anti-PD1 treatment relative to pre-PD-1 (L2FC) by RNA-seq (n=17 from 10 patients).

FIG. 3I depicts absolute expression (RPKM) for CCL19 and CXCL13 in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB) or no clinical benefit (NCB) from checkpoint blockade.

FIG. 3J depicts absolute expression (RPKM) for CCR7 and CXCR5, the respective receptors for CCL19 and CXCL13, in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB) or no clinical benefit (NCB) from checkpoint blockade.

FIG. 3K is a heat map that illustrates immune signatures (GSEA) in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients).

FIG. 3L depicts a Kaplan-Meier survival curve by CCL19/CXCL13 expression (high vs. low).

FIG. 3M depicts a Kaplan-Meier survival curve by four-way sorting using cutaneous melanoma (SKCM) TCGA data20 (logrank Mantel-Cox test).

FIG. 3N illustrates immune signatures (GSEA) in melanoma biopsy specimens (pre- and on-treatment) in clusters of patients with varying expression of CCL19 and CXCL13 in cutaneous melanoma (SKCM) TCGA.

FIG. 3O is a heatmap that illustrates an unsupervised hierarchical clustering of Day 3 PDOTS anti-PD1 induced cytokines, expressed as row normalized (L2FC; n=14), annotated by response to anti-PD-1 therapy and timing of sample collection.

FIG. 4A depicts a scheme of impact of TBK1/IKKε inhibition on cytokine production from tumor cells and T cells.

FIG. 4B depicts the chemical structure of Compound 1 with IC₅₀ towards TBK1/IKKE, and EC₅₀ in HCT116 cells.

FIG. 4C depicts cytokine heatmaps for CT26 spheroids (lacking immune cells) on Day 1, 3, and 6±Compound 1 (n=3, biological replicates) expressed as log 2 fold-change (L2FC) relative to vehicle control.

FIG. 4D is a dose-response curve for Compound 1 on IL-2 in human CD4 (n=3) and CD8 (n=5) T cells.

FIG. 4E is a dose-response curve for Compound 1 on IFNγ in human CD4 (n=3) and CD8 (n=5) T cells.

FIG. 4F depicts cytokine heatmaps for CT26 MDOTS treated with IgG+Cmpd1 (1 μM), αPD-1 (10 μg/mL), or αPD-1+Cmpd1 (1 μM) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG with vehicle control. 2-sided Welch's 2-sample t-test with unequal variance (α=0.05).

FIG. 4G is a chart that depicts live (AO=green)/dead (PI=red) quantification of CT26 MDOTS after 6 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 4H depicts imaging results corresponding to live (AO=green)/dead (PI=red) quantification of CT26 MDOTS after 6 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 4I depicts CT26 allograft tumor volume over time following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 4J depicts CT26 allograft percent change in tumor volume following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 4K depicts CT26 allograft percent survival following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 5A depicts common gating for viable CD45+ cells in immune cell profiling by multi-color flow cytometry experiments.

FIG. 5B depicts gating hierarchy for T cell lineage and phenotypic marker in immune cell profiling by multi-color flow cytometry experiments.

FIG. 5C depicts myeloid cell gating hierarchy in immune cell profiling by multi-color flow cytometry experiments.

FIG. 5D depicts gating for NK lineage and Tregs in immune cell profiling by multi-color flow cytometry experiments.

FIG. 6A depicts immune cell sub-populations in MC38 tumors and/or spheroids from immune cell profiling of MDOTS. Immune cell sub-populations from MC38 (a) bulk tumor (n=5) to S1, S2, S3 (n=6) were evaluated by flow cytometry, as in FIG. 1b (Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; *p<0.05; ns=not significant).

FIG. 6B depicts a Pearson correlation matrix using composite of 21 cell surface markers in MC38 tumor, S1, S2, and S3 spheroids.

FIG. 6C depicts immune cell sub-populations in B16F10 tumors and/or spheroids from immune cell profiling of MDOTS. Immune cell sub-populations from B16F10 (a) bulk tumor (n=5) to S1 (n=4), S2 (n=5), and S3 (n=4) evaluated by flow cytometry (Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; *p<0.05; ns=not significant).

FIG. 6D depicts CD45+ cells (% live cells) in MC38 (n=6), B16F10 (n=5), and CT26 (n=5) MDOTS (S2). Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; *p<0.05.

FIG. 6E depicts immune sub-populations (% CD45+ cells) in MC38 (n=6), B16F10 (n=5), and CT26 (n=5) MDOTS (S2). 2-way ANOVA with Tukey's multiple comparisons test, (α=0.05; *p<0.05, ***p<0.001, ****p<0.0001).

FIG. 6F depicts surface expression of T cell exhaustion markers (PD-1, CTLA-4, TIM-3) on CD4 and CD8 populations in PDOTS (n=40) from immune cell profiling of PDOTS.

FIG. 6G depicts surface expression of PD-L1 and PD-L2 on myeloid sub-populations, including granulocytic myeloid-derived suppressor cells (gMDSCs), monocytes, tumor-associated macrophages (TAMs), monocytic myeloid-derived suppressor cells (mMDSCs), and plasmacytoid dendritic cells (pDCs).

FIG. 6H depicts immune cell sub-populations of PDOTS fractions (S1, S2, S3) evaluated by flow cytometry, for CD45+ (n=8), CD3+ (n=8), CD4+ (n=7), CD8+ (n=7), CD14+ (n=7), and CD15+ (n=6). Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; ns=not significant.

FIG. 6I depicts antigen-experienced sub-population (CD45RO+), effector memory (CD45RO+CCR7−) subtype, and surface expression of T cell exhaustion markers (PD-1, CTLA-4, TIM-3) on CD4 populations in PDOTS fractions (n≥3; Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; ns=not significant).

FIG. 6J depicts antigen-experienced sub-population (CD45RO+), effector memory (CD45RO+CCR7−) subtype, and surface expression of T cell exhaustion markers (PD-1, CTLA-4, TIM-3) on CD8 populations in PDOTS fractions (n≥3; Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; ns=not significant).

FIG. 7A depicts immunofluorescence staining of MC38 MDOTS.

FIG. 7B depicts immunofluorescence staining of NSCLC PDOTS.

FIG. 7C depicts immunofluorescence staining of NSCLC PDOTS.

FIG. 7D depicts immunofluorescence staining for MC38 MDOTS stained for CD45+ immune cells (purple) and CD8+ T cells (yellow) with calcein (green) staining live cells and Hoechst (blue) staining all cell nuclei at Day 7 after treatment with IgG (10 μg/mL) or anti-PD-1 (10 μg/mL) (scale bar=20 μm).

FIG. 7E is a chart that depicts live/dead analysis of MC38 MDOTS±anti-PD-1 performed by independent lab (n=3, biological replicates).

FIG. 7F is a chart that depicts live/dead analysis of CT26 MDOTS performed on Day 6 following treatment with isotype IgG control (10 μg/mL) or anti-PD-1 (10 μg/mL)±anti-CD8 (10 μg/mL) (n=6, biological replicates; 2-way ANOVA with Tukey's multiple comparisons test; ****p<0.0001, ns=not significant).

FIG. 7G depicts a comparison of intratumoral and inter-tumoral heterogeneity evaluating CD8+ T cell counts (IF, performed on Day 4) and live/dead analysis (AO/PI staining) of CT26 MDOTS (Day 5).

FIG. 8A depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to αPD-1 grouped by Th1 and IFN-γ effector cytokines, (n=28; 2-sided, paired, t-test, α=0.05).

FIG. 8B depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to αPD-1 grouped by granulocyte chemoattractants, (n=28; 2-sided, paired, t-test, α=0.05).

FIG. 8C depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to αPD-1 grouped by IPRES immune suppressive cytokines, (n=28; 2-sided, paired, t-test, α=0.05).

FIG. 8D illustrates a comparison of PDOTS cytokine profiles after 3 days in standard growth conditions with and without isotype control IgG antibody (50 μg/mL) (n=2), performed using PDOTS derived from sample MGH-16 (melanoma).

FIG. 8E depicts CCL19 and CXCL13 levels (pg/mL) relative to the number of spheroids per device in control and treatment (αPD-1) conditions (R2=Pearson correlation coefficient).

FIG. 8F depicts results of biological replicates for MGH-16 PDOTS in response to PD-1 blockade (n=3, L2FC relative to untreated control on Day 3).

FIG. 8G depicts CCL19 and CXCL13 levels (pg/mL) from biological replicates for MGH-16 PDOTS in response to PD-1 blockade (n=3, L2FC relative to untreated control on Day 3).

FIG. 8H depicts the correlation between CCL19 and CXCL13 upregulation (log 2 fold-change relative to untreated control) in response to αPD-1, αCTLA-4, or αPD-1+αCTLA-4 (R2=Pearson correlation coefficient).

FIG. 8I illustrates the effect of culture in the microfluidic device on cytokine profile following αPD-1 treatment. Equal volumes of PDOTS from patient MGH-16 (in collagen hydrogels) were loaded for microfluidic device (or into a single well of a 96-well plate in equal volumes of culture media. Media was collected on Day 3 (control and αPD-1) for cytokine profiling. Induction of cytokines represented as fold-change relative to the untreated control.

FIG. 9A is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in DFCI-25 (melanoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 9B is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in MGH-12 (melanoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 9C is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in DFCI-16 (thyroid carcinoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 9D is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in DFCI-19 (pancreatic adenocarcinoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 10A depicts RNA-seq showing select cytokines, cytokine receptors, cytotoxic T cell (CTL) associated genes, and IPRES transcripts (L2FC relative to pre-treatment control in 10 sets of patient samples).

FIG. 10B depicts RNA-seq absolute expression (RPKM) for cytotoxic T cell effector associated genes (IFNG, IFNGR1, granzyme A, granzyme B) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients) from checkpoint blockade.

FIG. 10C depicts RNA-seq absolute expression (RPKM) for select IPRES genes in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients) from checkpoint blockade.

FIG. 10D depicts pre-treatment expression of CCL19 and CXCL13 in responders (n=15) and non-responders (n=13) to PD-1 blockade. Expression data is represented as transcripts per million (TPM) with error bars indicating standard deviation (ns=not significant; unpaired, 2-sided, Mann-Whitney test, α=0.05).

FIG. 10E depicts pre-treatment expression of CCL19 and CXCL13 in patients who experienced clinical benefit (CB, n=14), no clinical benefit (NCB, n=22), and no clinical benefit, but long-term survival (NCB+LTS, n=5) from ipilimumab (αCTLA-4). Expression data is represented as transcripts per million (TPM) with error bars indicating standard deviation (ns=not significant; Kruskal-Wallis with Dunn's multiple comparisons test, α=0.05).

FIG. 10F is a heatmap demonstrating log(2) fold change (on-αPD-1/pre-αPD-1) in expression of indicated cytokines.

FIG. 10G is a heatmap demonstrating log(2) fold change of plasma cytokines using matched plasma samples (on-treatment/pre-treatment) for responders (R; n=7) and non-responders (NR; n=4) to anti-PD-1 therapy.

FIG. 10H depicts four-way Kaplan-Meier survival curves by CCL19/CXCL13 expression (high-high, high-low, low-high, and low-low) using urothelial bladder carcinoma (BLCA), head & neck squamous cell carcinoma (HNSC), and breast carcinoma (BRCA) TCGA data (pairwise analysis using log-rank Mantel-Cox test, *p<0.05).

FIG. 11A depicts H&E imaging (10× objective) of tumor-associated tertiary lymphoid structure (TA-TLS), higher magnification (40× objective), and quantitation of TA-TLS identified in 52 H&E slides.

FIG. 11B depicts PDOTS divided into CCL19/CXCL13-high (n=14) and CCL19/CXCL13-low (n=14) by median L2FC (Mann-Whitney test, ****p<0.0001).

FIG. 11C depicts median immune cell composition (CD45+, CD4+, CD8+, CD14+, CD15+) between PDOTS with distinct ex vivo expression of CCL19/CXCL13 (high vs. low).

FIG. 11D depicts median immune cell composition (CD4+PD1+ and CD8+PD-1+) in CCL19/CXCL13 high vs. low PDOTS.

FIG. 11E depicts relative expression of CCL19 and CXCL13 by qRT-PCR in cancer-associated fibroblasts (CD45−CD90+), cancer-associated endothelial cells (CD31+CD144+), CD45− (cancer cells, etc.) and CD45+ immune cells following 4-way cell sorting (n=2, technical replicates from MGH-16).

FIG. 11F depicts immunohistochemical staining of CCL19, CXCL13, αSMA (cancer-associated fibroblasts), and CD31 (endothelial cells) in melanoma specimen (pt 422, on-treatment; 40× magnification, scale bar 400 μm).

FIG. 12A depicts mean cytokine changes from PDOTS following ex vivo PD-1 blockade in patients with clinical benefit (n=5; PR/SD) and without clinical benefit (n=9; MR/PD) from PD-1 blockade (*p<0.05).

FIG. 12B depicts four-way Kaplan-Meier survival curves by CX3CL1/CCL20 expression (high-high, high-low, low-high, and low-low) using melanoma TCGA data (pairwise analysis using log-rank Mantel-Cox test, α=0.05, ns=not significant).

FIG. 12C depicts composite IPRES6 score (sum of L2FC for CCL2, CCL7, CCL8, CCL13, IL-10) in response to ex vivo PD-1 blockade in PDOTS samples from patients with clinical benefit (PR/SD) and without clinical benefit (MR/PD) from PD-1 blockade.

FIG. 12D depicts heatmaps of Day 3 PDOTS anti-PD1 induced cytokines for samples DFCI-13, -16, -18, and -21 (serial sampling from same patient with metastatic papillary thyroid cancer), expressed as L2FC relative to untreated control.

FIG. 12E is a chart that depicts serial immune profiling of samples DFCI-13, -16, -18, -21, and -22 from the same patient undergoing indicated treatments.

FIG. 12F is a heatmap of relative anti-PD1 induced cytokine changes from MC38 and B16F10 MDOTS (L2FC relative to isotype control; n=3, biological replicates).

FIG. 12G is a chart that depicts absolute cytokine levels in CT26 MDOTS over time (n=3, biological replicates).

FIG. 12H depicts Live/Dead analysis at Day 6 in CT26 MDOTS treated with anti-CCL2±anti-PD-1 at Days 1, 3, and 6 (L2FC relative to isotype control; n=3, biological replicates).

FIG. 12I is a heatmap of relative cytokine changes in CT26 MDOTS treated with anti-CCL2±anti-PD-1 at Days 1, 3, and 6 (L2FC relative to isotype control; n=3, biological replicates).

FIG. 13A is a scheme that depicts chemical synthesis of Compound 1.

FIG. 13B is a chart that depicts IC₅₀ values for indicated enzymes treated with Compound 1.

FIG. 13C depicts an IC₅₀ curve for TBK1.

FIG. 13D depicts an IC₅₀ curve for IKKε (IKBKE).

FIG. 13E is a chart that depicts effect of Compound 1 on viability of CT26 spheroids lacking immune cells (n=3, biological replicates).

FIG. 13F illustrates fold-change in IL-2 levels produced by Jurkat cells with increasing doses of Compound 1.

FIG. 13G depicts change in tumor volume following re-implantation of CT26 and EMT-6 cells into the flanks of mice previously treated with anti-PD-L1+Compound 1.

FIG. 14A is a cytokine heatmap for MC38 MDOTS treated with IgG+Cmpd1 (1 μM), αPD-1 (10 μg/mL), or αPD-1+Cmpd1 (1 μM) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG (10 μg/mL) with vehicle control (DMSO 0.1%). 2-sided Welch's 2-sample t-test with unequal variance (α=0.05).

FIG. 14B is a cytokine heatmap for B16F10 MDOTS treated with IgG+Cmpd1 (1 μM), αPD-1 (10 μg/mL), or αPD-1+Cmpd1 (1 μM) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG (10 μg/mL) with vehicle control (DMSO 0.1%). 2-sided Welch's 2-sample t-test with unequal variance (α=0.05).

FIG. 14C is a chart that depicts live (AO=green)/dead (PI=red) quantification of MC38 MDOTS after 5 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 14D depicts MC38 allograft tumor volume waterfall plot following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 14E depicts percent survival following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 14F is a chart that depicts live (AO=green)/dead (PI=red) quantification of B16F10 MDOTS after 6 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (α=0.05, ns=not significant. Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 14G depicts quantification of small lung metastases in B16F10 tail vein injection model following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, 1-way ANOVA with Tukey's multiple comparison's test, ns=not significant).

FIG. 14H depicts quantification of medium lung metastases in B16F10 tail vein injection model following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, 1-way ANOVA with Tukey's multiple comparison's test, ns=not significant).

FIG. 14I depicts MB49 allograft tumor volume waterfall plot following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 14J depicts MB49 allograft tumor volume waterfall plot as a bar chart following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 14K depicts percent survival following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 15 depicts a table summary of Pilot RNA Extraction, QC, and Quantitation (left), and a representation bioanalyzer trac showing fully intact total RNA from MDOTS (right).

FIG. 16A is a sample-sample correlation of RNA-seq data collected from a variety of MC38 MDOTS treatment types (αPD-1, αPD-1+CD8, IFNγ, IgG, PD-1) at two distinct timepoints (Day 3, Day 6).

FIG. 16B provides two depictions of a principal components (PC) analysis of RNA-seq data collected from a variety of MC38 MDOTS treatment types (αPD-1, αPD-1+CD8, IFNγ, IgG, PD-1) at two distinct timepoints (Day 3, Day 6).

FIG. 16C depicts RNA-seq data collected from MC38 MDOTS sample treated with IFNγ on Day 6. Of note, several IFNγ genes are induced, including CXCL10, CXCL11, PD-L1, IDO1, and IDO2.

FIG. 16D depicts RNA-seq data collected from MC38 MDOTS sample treated with αPD-1 on Day 6. Of note, several novel targets and biomarkers are induced, including SOCS3, Pde4b, Pde4d, and Adcy5.

DETAILED DESCRIPTION

Among other aspects, the disclosure provides methods for evaluating tumor cell spheroids in a three-dimensional microfluidic device by monitoring a ratio of live cells to dead cells. In some aspects, the methods include steps of exposing separate aliquots of a tumor spheroid sample to different conditions, such as the inclusion or exclusion of a test compound.

As such, in some embodiments, the effects of a test compound can be evaluated by monitoring its effects on the ratio of live cells to dead cells. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid can be evaluated optically and reproducibly, to establish the effects of drugs on the tumor cells within the spheroids, while distinguishing the effects on tumor cells resulting from the act of culturing the tumor cells. Also provided are other methods for evaluating tumor sphere spheroids, including monitoring a chemical change, e.g., such as a change in nucleic acid expression, when separate aliquots of a tumor spheroid sample are exposed to different conditions, such as the inclusion or exclusion of a test compound.

As used herein, the term “tumor” refers to a neoplasm, i.e., an abnormal growth of cells or tissue and is understood to include benign, i.e., non-cancerous growths, and malignant; i.e., cancerous growths including primary or metastatic cancerous growths.

Examples of neoplasms include, but are not limited to, mesothelioma, lung cancer (e.g., small-cell lung cancer, non-small cell lung cancer), skin cancer (e.g., melanoma), stomach cancer, liver cancer, colorectal cancer, breast cancer, pancreatic cancer, prostate cancer, blood cancer, bone cancer, bone marrow cancer, and other cancers.

The term “tumor spheroid,” or “tumor cell spheroid” as used herein, refers to an aggregation of tumor cells constituting a small mass, or lump of tumor cells. In some embodiments, tumor spheroids are less than about 3 cm, less than about 2 cm, less than about 1 cm, less than about 5 mm, less than about 2.5 mm, less than about 1 mm, less than about 100 μm, less than about 50 μm, less than about 25 μm, less than about 10 μm, or less than about 5 μm in diameter. In some embodiments, the tumor spheroids have a diameter of 10 μm to 500 μm. In some embodiments, the tumor spheroids have a diameter of 40 μm to 100 μm. In some embodiments, the tumor spheroids have a diameter of 40 μm to 70 μm.

The term “primary tumor sample” as used herein refers to a sample comprising tumor material obtained from a subject having cancer. The term encompasses tumor tissue samples, for example, tissue obtained by surgical resection and tissue obtained by biopsy, such as for example, a core biopsy or a fine needle biopsy. The term also encompasses patient derived xenograft (PDX). Patient derived xenografts are created when cancerous tissue from a patient's primary tumor is implanted directly into an immunodeficient mouse (see, for example, Morton C L, Houghton P J (2007). “Establishment of human tumor xenografts in immunodeficient mice”. Nature Protocols 2 (2): 247-50; Siolas D, Hannon G J (September 2013). “Patient-derived tumor xenografts: transforming clinical samples into mouse models”. Cancer Research 73 (17): 5315-9). PDX mirrors patients' histopathological and genetic profiles. It has improved predictive power as preclinical cancer models, and enables the true individualized therapy and discovery of predictive biomarkers.

In some embodiments, the subject is a human. In some embodiments, the subject is a non-human mammal or a non-human vertebrate. In some embodiments, the subject is laboratory animal, a mouse, a rat, a rodent, a farm animal, a pig, a cattle, a horse, a goat, a sheep, a companion animal, a dog a cat, or a guinea pig.

In some embodiments, a tumor sample as used herein is derived from a subject known to have resistance or sensitivity to a particular therapeutic treatment. For example, in some embodiments, methods provided herein can identify novel combination therapies and/or novel single therapies that overcome resistance to a specified treatment, e.g., PD-1 inhibition in the treatment of cancer. In some embodiments, where PD-1 combination therapies are to be evaluated, tumor samples may be derived from one or more subjects having the same or varied levels of sensitivity to PD-1 inhibition therapy. In some embodiments, the tumor sample is derived from a B16F10 murine model. B16F10 is a murine model that is minimally sensitive to PD-1 blockade. In some embodiments, the tumor sample is derived from an MC38 murine model. MC38 is a murine model that is highly sensitive to PD-1 blockade relative to B16F10. In some embodiments, the tumor sample is derived from a CT26 murine model. CT26 is a murine model that is of an intermediate sensitivity relative to B16F10 and MC38 models. In some embodiments, methods provided herein comprises steps of evaluating a combination of two or more of tumor samples derived from B16F10, MC38, or CT26 models.

Tumor cell spheroids can be prepared by any method known in the art. Exemplary methods for preparing tumor cell spheroids are described in WO 2016/112172, the disclosure of which is incorporated herein by reference.

In some embodiments, the primary tumor sample is collected in a serum-supplemented medium, for example but not limited to, RPMI medium supplemented with 10% fetal bovine serum. The sample is then minced, i.e., cut or chopped into tiny pieces. In some embodiments, the sample is minced on ice. In some embodiments, the minced primary tumor sample comprises tumor pieces in the size of about 3 mm, 2.5 mm, 2.0 mm, 1.5 mm, 1.0 mm, 0.5, or 0.25 mm.

In some embodiments, the primary tumor sample is not frozen and thawed.

In some embodiments, minced primary tumor sample is frozen in a medium supplemented with serum and thawed prior to treating with the composition comprising the enzyme. In some embodiments, the minced primary tumor sample is frozen for at least 6 hours 12 hours, 24 hours, 2 days, 1 week or one month. In some embodiments, the minced primary tumor sample is frozen at −80° C. In some embodiments, the minced primary tumor sample is frozen in liquid nitrogen. In some embodiments, the minced primary tumor sample is frozen in a medium supplemented with serum. In some embodiments, the minced primary tumor sample is frozen in a mixture containing serum and solvent such as Dimethyl sulfoxide (DMSO). In some embodiments, the minced primary tumor sample is frozen in a mixture containing fetal bovine serum and Dimethyl sulfoxide (DMSO).

In some embodiments, the frozen minced primary tumor sample is thawed, i.e., defrosted, before treating the sample with a composition comprising an enzyme. In some embodiments, the minced primary tumor sample is thawed in a water bath kept at about 37° C. (e.g., 35° C., 36° C., 37° C., 38° C., or 39° C.). In some embodiments, the minced primary tumor sample is thawed at room temperature.

The minced primary tumor sample is treated with an enzyme mix to digest the tumor samples. In some embodiments, the composition comprising an enzyme includes collagenase. In some embodiments, the composition comprising an enzyme includes a serum-supplemented culture medium, insulin, one or more corticosteroids, one or more antibiotics, collagenase and optionally one or more growth factors. Serum-supplemented culture media, corticosteroids, antibiotics, and growth factors are well-known in the art. In some embodiments, the composition comprising an enzyme comprises DMEM or RPMI, fetal bovine serum, insulin, epidermal growth factor, hydrocortisone, Penicillin and/or Streptomycin, and collagenase. In some embodiments, the composition comprising an enzyme comprises further comprises a buffering agent such as 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES).

“Treating the minced primary tumor sample with a composition comprising an enzyme” comprises incubating the minced tumor samples with the enzyme composition for at least 1 hour. In some embodiments, the minced tumor samples are incubated with the enzyme mix for at least 2 hours, at least 4 hours, at least 6 hours, at least 8 hours, at least 10 hours, at least 12 hours, at least 15 hours or at least 24 hours. In some embodiments, the minced primary tumor sample is incubated with the enzyme mix at 25° C., 26° C., 27° C., 28° C., 29° C., 30° C., 31° C., 32° C., 33° C., 34° C., 35° C., 36° C., 37° C., 38° C., or 39° C. In some embodiments, the minced primary tumor sample is incubated with the enzyme mix at 37° C.

In some embodiments, the minced primary tumor sample is treated with the composition comprising the enzyme in an amount or for a time sufficient yield a partial digestion of the minced primary tumor sample. In some embodiments, the minced primary tumor sample is treated with the composition comprising the enzyme for 30 minutes to 15 hours at a temperature of 25° C. to 39° C.

Collecting tumor spheroids from the enzyme mix treated sample comprises centrifuging and washing the sample at least twice followed by isolating the digested tumor spheroids of the desired size. In some embodiments, the enzyme mix treated sample is centrifuged and washed using phosphate buffered saline (PBS) at least twice. Tumor spheroids of the desired size are collected using sieves. In some embodiments, the tumor spheroids having a diameter of 10 μm, 50 μm, 100 μm, 200 μm, 300 μm, 400 μm, 450 μm, and 500 μm are collected from the enzyme mix treated sample with the use of a sieve. In some embodiments, the tumor spheroids having a diameter of 40 m to 100 μm are collected from the enzyme mix treated sample with the use of a sieve. In some embodiments, the tumor spheroids having a diameter of 40 μm, 50 μm, 60 μm and 70 μm are collected from the enzyme mix treated sample with the use of a sieve.

The tumor spheroids having a desired diameter are collected by sieving the enzyme mix treated sample through cell strainers. In some embodiments, the tumor spheroids having a diameter of 10 μm to 500 μm are collected by sieving the enzyme mix treated sample via 500 m and 10 μm cell strainers to yield tumor spheroids having a diameter of 10 μm to 500 μm. In some embodiments, the tumor spheroids having a diameter of 40 m to 100 μm are collected by sieving the enzyme mix treated sample via 100 μm and 40 μm cell strainers to yield tumor spheroids having a diameter of 10 μm to 500 μm. The tumor spheroids of the desired diameter are collected and suspended in a biocompatible gel. Examples of biocompatible gel include collagen, BD Matrigel™ Matrix Basement Membrane, or fibrin hydrogel (e.g., fibrin hydrogel generated from thrombin treatment of fibrinogen).

In some embodiments, the collected tumor spheroids are not frozen and then thawed before suspending in the biocompatible gel. In some embodiments, the collected tumor spheroids are introduced into the three-dimensional cell culture device within less than 2 hours, less than 1 hour, less than 30 minutes, less than 20 minutes, less than 10 minutes, or less after collection.

In some embodiments, the collected tumor spheroids are frozen in a freezing medium and then thawed before suspending in the biocompatible gel. In some embodiments, the collected tumor spheroids are frozen for at least 6 hours 12 hours, 24 hours, 2 days, 1 week or one month. In some embodiments, the collected tumor spheroids are frozen at −80° C. In some embodiments, the collected tumor spheroids are frozen in liquid nitrogen. In some embodiments, the collected tumor spheroids are frozen at −80° C. overnight, and then transferred to liquid nitrogen for storage. In some embodiments, the collected tumor spheroids are frozen in a medium supplemented with serum. In some embodiments, the collected tumor spheroids are frozen in a mixture containing culture medium such as DMEM or RPMI, fetal bovine serum and solvent such as Dimethyl sulfoxide (DMSO). The frozen spheroids are thawed, for example overnight at 4° C., and then suspended in the biocompatible gel.

The tumor spheroids are cultured, i.e., grown, in a three dimensional (3D) microfluidic device. In some embodiments, the tumor spheroids are cultured with endothelial cells, such as human umbilical vein endothelial cells (HUVECs). In some embodiments, the tumor spheroids are cultured without endothelial cells. In some embodiments, the tumor spheroids are cultured with or without endothelial cells for at least 1 day, at least 2 days, at least 4 days, at least 6 days, at least 1 week, or at least 2 weeks.

3D microfluidic devices are known in the art and include, for example, but not limited to, the devices described in US 2013/0143230, EP2741083, US 2014/0057311, U.S. Pat. No. 8,748,180, and WO 2016/112172, the disclosures of which are incorporated by reference herein.

In some embodiments, a 3D microfluidic device refers to a device that comprises one or more fluid channels flanked by one or more gel cage regions, wherein the one or more gel cage regions comprises the biocompatible gel in which the tumor spheroids are embedded, and wherein the device recapitulates, i.e., mimics, the in vivo tumor microenvironment. In order to facilitate visualization, the microfluidic device is typically comprised of a substrate that is transparent to light, referred to herein as “an optically transparent material”. As will be appreciated by those of skill in the art, suitable optically transparent materials include polymers, plastic, and glass. Examples of suitable polymers are polydimethylsiloxane (PDMS), poly(methyl methacrylate) (PMMA), polystyrene (PS), SU-8, and cyclic olefin copolymer (COC). In some embodiments, all or a portion of the device is made of a biocompatible material, e.g., the material is compatible with, or not toxic or injurious to, living material (e.g., cells, tissue).

The fluid channel can be used to contain a (one or more) fluid (e.g., cell culture media), cells such as endothelial cells, cellular material, tissue, fluorophore dyes, and/or compounds (e.g., drugs) to be assessed, while the gel cage regions may be used to contain a gel (e.g., biologically relevant gel, such as collagen, Matrigel™, or fibrin hydrogel (e.g., fibrin hydrogel generated from thrombin treatment of fibrinogen)). In some embodiments, the 3D microfluidic device comprises the device described in US 2014/0057311, the disclosure of which is incorporated by reference herein. In particular, paragraphs [0056] to [0107] which describe the regions, channels, chambers, posts, and arrangement of posts, and paragraphs [0127] to [0130] which describe the methods of making the device are incorporated by reference herein.

In some embodiments, the method for identifying a compound for treating cancer, comprises culturing a first and second aliquot of tumor cell spheroids in a three-dimensional microfluidic device as described herein in the presence and absence of one or more test compounds, detecting a change in the ratio of live cells to dead cells in the aliquots of tumor cell spheroids.

In some embodiments, the change in the ratio of live cells to dead cells in the aliquots of tumor cell spheroids is monitored by measuring the total fluorescence emitted by each of the first and second fluorophore dyes. Accordingly, in some embodiments, the dead cell fluorescence and the live cell fluorescence can be added together to yield a live and dead cell total. In some embodiments, the amount of dead cells may be expressed as a percentage of the dead cell fluorescence to the total fluorescence. In some embodiments, the amount of live cells can be expressed as a percentage of the live cell fluorescence to the total. In some embodiments, the dead cell fluorescence and the live cell fluorescence can be expressed as a ratio. For example, in some embodiments, the ratio is expressed as dead cells/live cells or live cells/dead cells. In this manner, expressing as a ratio provides a standardized method of evaluating tumor cell spheroids.

In some embodiments, proliferation and/or dispersion of the tumor cell spheroids are also assessed.

In some embodiments, the method for identifying a compound or combination of compounds for treating cancer, comprises obtaining tumor spheroids from an enzyme treated tumor sample, suspending a first aliquot of the tumor spheroids in biocompatible gel, and suspending a second aliquot of the tumor spheroids in biocompatible gel. In some embodiments, the method further comprises placing the first aliquot of the tumor spheroids in biocompatible gel in a first three-dimensional device, and contacting the first aliquot with a first fluorophore dye selective for dead cells and a second fluorophore dye selective for live cells, where the first fluorophore dye emits fluorescence at a first wavelength when bound to a dead cell and the second fluorophore dye emits fluorescence at a second wavelength different from the first wavelength when bound to a live cell. In some embodiments, the method further comprises measuring total fluorescence emitted by each of the first and second fluorophore dyes in the first aliquot. In some embodiments, the method further comprises culturing the second aliquot in a second three-dimensional device, contacting the second aliquot with the first fluorophore dye and the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye. In some embodiments, the method further comprises measuring total fluorescence emitted by each of the first and second fluorophore dyes in the second aliquot, wherein an increase or decrease in the ratio of live cells to dead cells in each of the aliquots may be assessed.

“Culturing patient-derived tumor cell spheroids in the presence of the test compound” comprises introducing the test compound into the one or more fluid channels of the device described herein, wherein the one or more gel cage regions of the device comprises a gel in which the tumor spheroids are embedded; and culturing the tumor spheroids under suitable culture conditions. Suitable conditions include growing the tumor cell spheroids under standard cell culture conditions (e.g. at 37° C. in a humidified atmosphere of >80% relative humidity air and 5 to 10% CO₂).

In some embodiments, techniques provided herein relate to evaluating the effects of one or more therapeutic treatments in a tumor cell spheroid culture. In some embodiments, changes in the tumor cell spheroid culture are evaluated using one or more luminescent probes (e.g., one or more fluorescent dyes). For example, in some embodiments, methods described herein comprise steps of contacting a tumor cell spheroid culture with a first fluorophore dye and a second fluorophore dye that each selectively bind to a cell type that is different from the other, and where the fluorophore dyes emit fluorescence at different wavelengths when bound to the respective cell types. In some embodiments, the first fluorophore dye is selective for dead cells and the second fluorophore dye is selective for live cells. In some embodiments, the first fluorophore dye is selective for live cells and the second fluorophore dye is selective for dead cells.

In some embodiments, one or more fluorophore dye (e.g., one or more of a first fluorophore dye, one or more of a second fluorophore dye) is introduced into the one or more fluid channels of the cell culture device. The techniques provided in the present disclosure are envisioned to be compatible with any suitable fluorophore dye (e.g., fluorophore-containing dyes, stains, fluorescent labels, etc.). Suitable fluorophore dyes are known in the art and can be selected by a practitioner in view of a desired application of the techniques described herein. For example, in some embodiments, the one or more fluorophore dyes utilized in the techniques described herein can be compatible with staining under fixed or non-fixed conditions.

Fluorophore dyes that can be used for the detection of dead cells in non-fixed conditions include, by way of example and not limitation, DNA-dependent stains such as propidium iodide, DRAQ7, and 7-AAD. Fluorophore dyes that can be used for the detection of dead cells in either fixed or non-fixed conditions include, by way of example and not limitation, dyes listed in Table 1.

TABLE 1 Examples of dyes to stain for dead cells Excitation Emission Dye (max) (max) Propidium iodide 540 nm 620 nm DRAQ7 600 nm 697 nm 7-AAD 550 nm 645 nm eBioscience Fixable Viability Dye eFluor ® 455UV 350 nm 455 nm eBioscience Fixable Viability Dye eFluor ® 450 405 nm 450 nm eRinscience Fixable Viability Dye eFluor ® 506 405 nm 506 nm eBioscience Fixable Viability Dye eFluor ® 520 488 nm 522 nm eBioscience Fixable Viability Dye eFluor ® 660 633 nm 660 nm eBioscience Fixable Viability Dye eFluor ® 780 633 nm 780 nm BioLegend Zombie Aqua ™ 382 nm 510 nm BioLegend Zombie NIR ™ 718 nm 746 nm BioLegend Zombie Red ™ 600 nm 624 nm BioLegend Zombie Violet ™ 400 nm 423 nm BioLegend Zombie UV ™ 362 nm 459 nm BioLegend Zombie Yellow ™ 396 nm 572 nm

The techniques provided in the present disclosure are envisioned to be compatible with any suitable fluorophore dye selective for live cells known in the art. Fluorophore dyes that can be used for the detection of live or fixed cells include, by way of example and not limitation, DNA-dependent stains such as acridine orange, nuclear green LCS1 (ab138904), DRAQ5 (ab108410), CyTRAK Orange, NUCLEAR-ID Red DNA stain (ENZ-52406), and SiR700-DNA. Examples of non-DNA-dependent fluorophore dyes that stain for live cells are known in the art and include, by way of example and not limitation, calcein AM, calcein violet AM, and calcein blue AM. Fluorophore dyes that can be used for the detection of live or fixed cells include, by way of example and not limitation, dyes shown in Table 2.

TABLE 2 Examples of dyes to stain for live cells Dye Excitation Emission Vybrant ® DyeCycle ™ Violet UV, 405 nm 437 Vybrant ® DyeCycle ™ Green 488 nm 534 Vybrant ® DyeCycle ™ Orange 488, 532 nm 563 Vybrant ® DyeCycle ™ Ruby 188, 633/5 nm 686 acridine orange 500 nm 526 nm nuclear green LCS1 (ab138904) 503 nm 526 nm DRAQ5 (ab108410) 647 nm 681 nm CyTRAK Orange 488-550 nm 610 nm NUCLEAR-ID Red DNA stain 566 nm 650 nm (ENZ-52406) SiR700-DNA 689 nm 716 nm calcein AM 495 nm 515 nm calcein violet AM 408 nm 450 nm calcein blue AM 360 nm 445 nm

Additionally, two-color cell viability assays are available and may be used with the techniques described herein. Examples of live/dead cytotoxicity kits include, by way of example and not limitation, kits shown in Table 3.

TABLE 3 Examples of kits containing dyes to stain for both live/dead cells Kit Name Platform Fluorescent Dyes Ex/Em (nm) Em Colors LIVE/DEAD FC, FM, M calcein AM 494/517 Green Viability/Cytotoxicity Kit for ethidium 517/617 (Live) mammalian cells homodimer-1 Red (Dead) LIVE/DEAD Cell-Mediated FC, FM, M DiOC₁₈(3) 484/501 Green Cytotoxicity Kit for animal propidium 536/617 (Live) cells, 2000 assays iodide Red (Dead) LIVE/DEAD Sperm Viability FC, FM SYBR ™ 14 485/517 Green Kit 200-1,000 assays dye propidium 536/617 (Live) iodide Red (Dead) LIVE/DEAD Cell Vitality FC, FM, M SYTOX ™ 488/530 Green Assay Kit C₁₂- Green dye 488/575 (Dead) resazurin/SYTOX ™ Green C12-resazurin Red 1,000 assays (Live)

Changes in the tumor cell spheroid culture which predict or demonstrate a reduction in proliferation and/or dispersion of the tumor cell spheroids in the presence or absence of the test compound can be detected using known methods in the art, such as, chemical or physical methods, or a combination thereof.

As described herein, a tumor cell spheroid sample is evaluated by analyzing the relative amounts of live cells and dead cells in separate aliquots of the sample. In some embodiments, the relative amounts of live cells and dead cells in an aliquot is determined by fluorescence measurement. For example, in some embodiments, fluorescence measurement comprises total fluorescence acquisition of the emissions detected from a first fluorophore dye that selectively binds dead cells and a second fluorophore dye that selectively binds live cells. Based on such measurements, the relative emission levels can be parsed out to provide the amount of live cells relative to the amount of dead cells in the aliquot.

In some embodiments, the relative amounts or ratio of live cells to dead cells in an aliquot can be expressed as a percentage of the total fluorescence, such that: [(% live cells)+(% dead cells)=100%] In some embodiments, the relative levels of live cells and dead cells in a first aliquot is compared to a similar measurement obtained for a second aliquot that has been treated with a test compound. An increase in (% dead cells) in the presence of the test compound compared to the first aliquot is indicative that the test compound is effective for inducing cell death. In some embodiments, the percentage of dead cells in the presence of an effective test compound is increased relative to the absence of the test compound by about 5%, by about 10%, by about 15%, by about 20%, by about 25%, by about 30%, by about 35%, by about 40%, by about 50%, by about 60%, by about 70%, by about 80%, by about 90%, or greater.

In some embodiments, a change in the tumor cell spheroid culture can further be detected visually, e.g., using confocal microscopy imaging. The images obtained can be analyzed as described in Aref et al. Integr Biol (Camb). 2013 February; 5(2):381-9, the disclosure of which is incorporated by reference in its entirety. In particular, the paragraphs on pages 387-388 relating to image acquisition and analysis (normalized dispersion, Δ/Δ0, and normalized cell number (N/N0)) are incorporated by reference in their entirety.

In some embodiments, the change in the tumor cell spheroid culture is a clustering of immune cells around one or more tumor cell spheroids in the culture. In some embodiments, the change in the tumor cell spheroid culture is a decrease in size and/or number of cells of one or more tumor cell spheroids in the culture.

In some embodiments, the change in the tumor cell culture is further detected chemically. For example, in some embodiments, the change in the tumor cell spheroid culture is determined by detection of the presence of a biological molecule secreted into the culture supernatant. In some embodiments, the biological molecule is a protein, carbohydrate, lipid, nucleic acid, metabolite, or a combination thereof. In some embodiments, the biological molecule is a chemokine or a cytokine. In some embodiments, the cytokine is a growth factor (see e.g., Example 2). In some embodiments, the biological molecule is known to be associated with activation of the immune system or otherwise an enhancement of the immune response.

In some embodiments, the detected biological molecule(s) involves single cell sequencing of T cell receptors on tumor spheroid associated CD4 and CD8 T cells that become activated in the device.

In some embodiments, a sample of tumor cell spheroid culture supernatant may be obtained from the 3D culture device. In some embodiments, a secreted biological molecule or a profile of secreted biological molecules, e.g., a cytokine profile or chemokine profile, may be detected in the tumor cell spheroid culture supernatant.

Methods for detecting secreted biological molecules are known in the art. Exemplary assays and cytokines are disclosed, for example, in WO 2016/112172, the disclosure of which is incorporated herein by reference.

In some embodiments, a sample of tumor cell spheroid is analyzed by nucleic acid content. For example, it is possible to analyze extracellular nucleic acids, e.g., nucleic acids present in a culture medium of a tumor cell spheroid sample using methods known in the art. Alternatively, nucleic acids can be isolated from cells in a cultured sample using methods known in the art. In some embodiments, such analysis can be used to assess gene expression, e.g., to evaluate the expression of genes associated with cytotoxicity, such as cytokines and cytokine receptors. In some embodiments, the cytokines are growth factors (see e.g., Example 2). In some embodiments, DNA and/or RNA (e.g., mRNA, rRNA, tRNA, etc.) from a sample may be analyzed.

In some embodiments, RNA content of a sample is analyzed using RNA sequencing (RNA-seq). RNA-seq is a reliable, scalable, and comprehensive method to evaluate transcriptomic changes in the tumor immune microenvironment. The use of RNA-seq enables a broad and comprehensive analysis of changes in the tumor immune microenvironment associated with response and resistance to immune checkpoint blockade and furthermore can readily be applied to molecular targeted therapies, combination therapies, engineered immune cells, and other related applications. In some embodiments, RNA content is analyzed using single-cell RNA-seq methodologies. In some embodiments, analysis by nucleic acid content will be utilized for medium- and high-throughput assay development.

In some embodiments, the test compound inhibits epithelial-mesenchymal transition (EMT). In some embodiments, the test compound is a small molecule compound. In some embodiments, the methods described herein are used to screen a library of test compounds, for example, a library of chemical compounds. In some embodiments, the test compound comprises a nucleic acid molecule, for example, a DNA molecule, an RNA molecule, or a DNA/RNA hybrid molecule, single-stranded, or double-stranded. In some embodiments, the test compound comprises an RNAi compound, for example, an antisense-RNA, an siRNA, an shRNA, a snoRNA, a microRNA (miRNA), or a small temporal RNA (stRNA). In some embodiments, the test compound comprises an aptamer. In some embodiments, the test compound comprises a protein or peptide. In some embodiments, the test compound comprises an antibody or an antigen-binding antibody fragment, e.g., a F(ab′)2 fragment, a Fab fragment, a Fab′ fragment, or an scFv fragment. In some embodiments, the antibody is a single domain antibody. In some embodiments, the compound comprises a ligand- or receptor-binding protein. In some embodiments, the compound comprises a gene therapy vector.

In some embodiments, more primary tumor cell spheroids are cultured in the presence of more than one compound, e.g., a first test compound and a second test compound, optionally a third test compound, fourth compound, etc.

In some embodiments, a test compound is an anti-cancer compound. In some embodiments a test compound is a chemotherapeutic compound, an immunomodulatory compound, or radiation.

Exemplary chemotherapeutic compounds include asparaginase, busulfan, carboplatin, cisplatin, daunorubicin, doxorubicin, fluorouracil, gemcitabine, hydroxyurea, methotrexate, paclitaxel, rituximab, vinblastine, vincristine, etc. In some embodiments, a test compound is a vinca alkaloid, e.g., vinblastine, vincristine, vindesine, vinorelbine. In some embodiments, a test compound is an alkylating compound, e.g., cyclophosphamide, decarbazine, melphalan, ifosfamide, temozolomide. In some embodiments, a test compound is an antimetabolite, e.g., folic acid antagonists, pyrimidine analogs, purine analogs or adenosine deaminase inhibitor, e.g., fludarabine. In some embodiments, a test compound is an mTOR inhibitor. In some embodiments, a test compound is a proteasome inhibitor, e.g., aclacinomycin A, gliotoxin or bortezomib.

In some embodiments, a test compound is a small molecule inhibitor, e.g., a TBK1 inhibitor, a MEK inhibitor, a FAK inhibitor, a BRD/BET inhibitor, a CDK 4/6 inhibitor, an HDAC inhibitor, a DNMT inhibitor (or hypomethylating compound), a MET inhibitor, an EGFR inhibitor, or a BRAF inhibitor. In some embodiments, a test compound is a kinase inhibitor, e.g., a TBK1 inhibitor, a MEK inhibitor, a FAK inhibitor, or a CDK 4/6 inhibitor. For example, TBK-1 inhibitors are known in the art, e.g., Yu, T., et al. “TBK1 inhibitors: a review of patent literature (2011-2014)” Exp. Opin. On Ther. Patents 25(12); Hasan, M., et al. J. Immunol. 195(10):4573-77; and US20150344473, the contents of each of which are incorporated herein by reference.

Exemplary immunomodulatory compounds include immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of: CTLA-4, PD-1, PD-L1, TIM3, LAG3, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GAL9, A2aR, and VISTA. In some embodiments, the immune checkpoint inhibitor is a peptide, antibody, interfering RNA, or small molecule. In some embodiments, the immune checkpoint inhibitor, e.g., inhibitor, is a monoclonal antibody, or an Ig fusion protein. In some embodiments, the immune checkpoint inhibitor is an antibody or an antigen binding fragment thereof. In some embodiments, the immune checkpoint inhibitor is an anti-PD-1 antibody.

In some embodiments, the immune checkpoint inhibitor inhibits PD1. In humans, programmed cell death protein 1 (PD-1) is encoded by the PDCD1 gene. PDCD1 has also been designated as CD279 (cluster of differentiation 279). This gene encodes a cell surface membrane protein of the immunoglobulin superfamily. PD-1 is a 288 amino acid cell surface protein molecule. PD-1 has two ligands, PDL1 and PD-L2, which are members of the B7 family. PD-1 is expressed on the surface of activated T cells, B cells, and macrophages. PD-1 is expressed in pro-B cells and is thought to play a role in their differentiation. See T. Shinohara 5 et al., Genomics 23 (3): 704-6 (1995). PD-1 is a member of the extended CD28/CTLA-4 family of T cell regulators. (Y. Ishida et al., “EMBO J. 11 (11): 3887-95, (1992)). PD-1 may negatively regulate immune responses. PD1 limits autoimmunity and the activity of T cells in peripheral tissues at the time of an inflammatory response to infection.

An immune checkpoint inhibitor that inhibits PD-1, or a PD-1 antagonist, as used herein is a molecule that binds to PD-1 and inhibits or prevents PD-1 activation. Without wishing to be bound by theory, it is believed that such molecules block the interaction of PD-1 with its ligand(s) PD-L1 and/or PD-L2.

PD-1 activity may be interfered with by antibodies that bind selectively to and block the activity of PD-1. The activity of PD-1 can also be inhibited or blocked by molecules other than antibodies that bind PD-1. Such molecules can be small molecules or can be peptide mimetics of PD-L1 and PD-L2 that bind PD-1 but do not activate PD-1. Molecules that antagonize PD-1 activity include those described in U.S. Publications 20130280265, 20130237580, 20130230514, 20130109843, 20130108651, 20130017199, and 20120251537, 2011/0271358, EP 217095911, the entire disclosures of which are incorporated herein by reference. See also M. A. Curran, et al., Proc. Natl. Acad. Sci. USA 107, 4275 (2010); S. L. Topalian, et al., New Engl. J. Med. 366, 2443 (2012); J. R. Brahmer, et al., New Engl. J. Med. 366, 2455 (2012); and D. E. Dolan et al., Cancer Control 21, 3 (2014). Herein, PD-1 antagonists include: nivolumab, also known as BMS-936558 (Bristol-Meyers Squibb, and also known as MDX-1106 or ONO-4538), a fully human IgG4 monoclonal antibody against PD-1; pidilizumab, also known as CT-011 (CureTech), a humanized IgG1 monoclonal antibody that binds PD-1; MK-3475 (Merck, and also known as SCH 900475), an anti-PD-1 antibody; and pembrolizumab (Merck, also known as MK-3475, lambrolizumab, or Keytruda), a humanized IgG4-kappa monoclonal antibody with activity against PD-1. Compounds that interfere bind to the DNA or mRNA encoding PD-1 also can act as PD-1 inhibitors. Examples include a small inhibitory anti-PD-1 RNAi, an anti-PD-1 antisense RNA, or a dominant negative protein. PD-L2 fusion protein AMP-224 (codeveloped by Glaxo Smith Kline and Amplimmune) is believed to bind to and block PD-1.

In some embodiments, the immune checkpoint inhibitor inhibits PD-L1. In humans, programmed death-ligand 1 (PD-L1), also known as B7 homolog 1 (B7-H1) or cluster of differentiation 274 (CD274), is a 40 kDa type 1 transmembrane protein that is encoded by the CD274 gene. Foreign antigens normally induce an immune response triggering proliferation of antigen-specific T cells, such as antigen-specific CD8+ T cells. PD-L1 is an immune checkpoint inhibitor that may block or lower such an immune response. PD-L1 may play a major role in suppressing the immune system during events such as pregnancy, tissue allografts, autoimmune disease, and other disease states, such as hepatitis and cancer. The PD-L1 ligand binds to its receptor, PD-1, found on activated T cells, B cells, and myeloid cells, thereby modulating activation or inhibition. In addition to PD-1, PD-L1 also has an affinity for the costimulatory molecule CD80 (B7-1). Upon IFN-γ stimulation, PDL1 is expressed on T cells, natural killer (NK) cells, macrophages, myeloid dendritic cells (DCs), B cells, epithelial cells, and vascular endothelial cells.

PD-L1 activity may be blocked by molecules that selectively bind to and block the activity of PD-L1. Anti-PD-L1 antibodies block interactions between PD-L1 and both PD-1 and B7-1 (also known as CD80). Block means inhibit or prevent the transmission of an inhibitory signal mediated via PD-L1. PD-L1 antagonists include, for example: BMS-30 936559, also known as MDX-1105 (Bristol-Meyers Squibb), a fully human, high affinity, immunoglobulin (Ig) G4 monoclonal antibody to PD-L1; MPDL3280A, also known as RG7446 or atezolizumab (Genentech/Roche), an engineered human monoclonal antibody targeting PDL1; MSB0010718C, also known as avelumab (Merck), a fully human IgG1 monoclonal antibody that binds to PD-L; and MED1473 (AstraZeneca/MedImmune), a human immunoglobulin (Ig) G1K monoclonal antibody that blocks PD-L1 binding to its 5 receptors. Compounds that bind to the DNA or mRNA encoding PD-L1 also can act as PD-L1 inhibitors, e.g., small inhibitory anti-PD-L1 RNAi, small inhibitory anti-PD-L1 RNA, anti-PD-L1 antisense RNA, or dominant negative PD-L1 protein. Antagonists of or compounds that antagonize PD-L1, e.g., anti-PD-L1 antibodies and PD-L1 antagonists, may include, but are not limited to those previously mentioned and any of those that are disclosed in Stewart et al., 2015, 3(9):1052-62; Herbst et al., 2014, Nature 515:563-567; Brahmer et al., N Engl J Med 2012; 366:2455-2465; U.S. Pat. No. 8,168,179; US20150320859; and/or US20130309250, all incorporated herein by reference.

In some embodiments, the immune checkpoint inhibitor inhibits CTLA-4. CTLA-4 (also known as CTLA-4 or cluster of differentiation 152 (CD152)), is a transmembrane glycoprotein that, in humans, is encoded by the CTLA-4 gene. CTLA-5 4 is a member of the immunoglobulin superfamily, which is expressed on the surface of helper T cells and is present in regulatory T cells, where it may be important for immune function. CTLA-4, like the homologous CD28, binds to B7 molecules, particularly CD80/B7-1 and CD86/B7-2 on antigen-presenting cells (APCs), thereby sending an inhibitory signal to T cells. CTLA-4 functions as an immune checkpoint that inhibits the immune system and is important for maintenance of immune tolerance.

CTLA-4 activity may be blocked by molecules that bind selectively to and block the activity of CTLA-4 or that bind selectively to its counter-receptors, e.g., CD80, CD86, etc. and block activity of CTLA-4. Blocking means inhibit or prevent the transmission of an inhibitory signal via CTLA-4. CTLA-4 antagonists include, for example, inhibitory antibodies directed to CD80, CD86, and/or CTLA-4; small molecule inhibitors of CD80, CD86, and CTLA-4; antisense molecules directed against CD80, CD86, and/or CTLA-4; adnectins directed against CD80, CD86, and/or CTLA-4; and RNAi inhibitors (both single and double stranded) of CD80, CD86, and/or CTLA-4.

Suitable CTLA-4 antagonists and/or anti-CTLA-4 antibodies include humanized anti-CTLA-4 antibodies, such as MDX-010/ipilimumab (Bristol-Meyers Squibb), tremelimumab/CP-675,206 (Pfizer; AstraZeneca), and antibodies that are disclosed in PCT Publication No. WO 2001/014424, PCT Publication No. WO 2004/035607, U.S. Publication No. 2005/0201994, European Patent No. EP 1212422 B1, U.S. Pat. Nos. 5,811,097, 5,855,887, 6,051,227, 6,984,720, 7,034,121, 8,475,790, U.S. Publication Nos. 2002/0039581 and/or 2002/086014, the entire disclosures of which are incorporated herein by reference. Other anti-CTLA-4 antibodies and/or CTLA-4 antagonists that can be used in a method of the present disclosure include, for example, those disclosed in Hurwitz et al., Proc. Natl. Acad. Sci. USA, 95(17):10067-10071 (1998); Camacho et al., J. Clin. Oncology, 22(145): Abstract No. 2505 (2004) (antibody CP9675206); Mokyr et al., Cancer Res., 58:5301-5304 (1998), and Lipson and Drake, Clin Cancer Res; 17(22) Nov. 15, 2011; U.S. Pat. No. 8,318,916; and/or EP1212422B1, all of which are herein incorporated by reference, in their entireties.

In some embodiments, the immune checkpoint inhibitor inhibits VISTA. V-domain Ig suppressor of T cell activation (VISTA), (also known as PD-II1, PD-1 homolog, or Diesl), is a negative regulator of T cell function. VISTA is a 309 aa type I transmembrane protein that is composed of seven exons, it has one Ig-V like domain, and its sequence is similar to the Ig-V domains of members of CD28 and B7 families. VISTA is highly expressed in the tumor microenvironment (TME) and on hematopoietic cells. It is also expressed on macrophages, dendritic cells, neutrophils, natural killer cells, and naive and activated T cells. Its expression is highly regulated on myeloid antigen-presenting cells (APCs) and T cells, while lower levels are found on CD4+ T cells, CD8+ T cells, and Treg cells. VISTA shows some sequence homology to the PD-1 ligand, PD-L1, however the two immune checkpoint inhibitors are structurally different and have different signaling pathways. VISTA blockade has been shown to enhance antitumor immune responses in mice, while in humans, blockade of the related PD-1 pathway has shown great potential in clinical immunotherapy trials. VISTA is a negative checkpoint regulator that suppresses T-cell activation and its blockade may be an efficacious immunotherapeutic strategy for human cancer. VISTA (Wang et al., 2011. JEM. 208(3):577-92; Lines et al., 2014. Cancer Res. 74(7):1924-32; Kondo et al. 2015. J. of Immuno. V194; WO2011120013; US20140105912; US20140220012; US20130177557, US20130177557, incorporated by reference herein, in their entireties).

VISTA activity may be blocked by molecules that selectively bind to and block the activity of VISTA. Molecules or compounds that are VISTA antagonists include peptides that bind VISTA, antisense molecules directed against VISTA, single- or doublestranded RNAi molecules targeted to degrade or inhibit VISTA, small molecule inhibitors of VISTA, anti-VISTA antibodies, inhibitory antibodies directed to VISTA, and humanized antibodies that selectively bind and inhibit VISTA. Antagonists of or compounds that antagonize VISTA, e.g., anti-VISTA antibodies and VISTA antagonists, are not limited to, but may include any of those that are disclosed in Liu et al. 2015. PNAS. 112(21):6682-6687; Wang et al., 2011. JEM. 208(3):577-92; Lines et al., 2014. Cancer Res. 74(7):1924-32; Kondo et al. 2015. J. of Immuno. V194; WO2015097536, EP2552947, WO2011120013, US20140056892, U.S. Pat. No. 8,236,304, WO2014039983, US20140105912, US20140220012, US20130177557; WO2015191881; US20140341920; CN105246507; and/or US20130177557, all of which are incorporated by reference herein, in their entireties.

In some embodiments, the immune checkpoint inhibitor inhibits TIM-3. In some embodiments, the immune checkpoint inhibitor inhibits LAG-3.

In some embodiments, a combination of test compounds are tested in the cell culture. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a CTLA-4 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a LAG-3 inhibitor.

In some embodiments, the combination of immune checkpoint inhibitors includes a PD-L1 inhibitor and a CTLA-4 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD-L1 inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD-L1 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a TIM-3 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor, a CTLA-4 inhibitor, and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor, a CTLA-4 inhibitor, and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor, a TIM-3 inhibitor, and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor, a TIM-3 inhibitor, and a LAG-3 inhibitor.

In some embodiments, the combination of test compounds includes an immune checkpoint inhibitor and a small molecule compound. In some embodiments, the combination of test compounds includes an immune checkpoint inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a PD-1 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a PD-L1 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a CTLA-4 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a VISTA inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a TIM-3 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a LAG-3 inhibitor and a TBK-1 inhibitor.

In some embodiments, an immune activating compound is a CD28 antagonist, e.g., an anti-CD28 antibody. An antibody, or immunoglobulin, is a glycoprotein containing two identical light chains (L chains), each containing approximately 200 amino acids, and two identical heavy chains (H chains), which generally are at least twice as long as the L chains. The paratope of the antibody is specific for a particular epitope of an antigen, and their spacial complementarity (binding) “tags” the microbe for further action or neutralize its actions directly. The antibody communicates with other components of the immune response via its crystallizable fragment (Fc) region, which includes a conserved glycosylation site. There are five Fc regions, resulting in the five different antibody isotypes: IgA, IgD, IgE, IgG, and IgM. IgD functions as an antigen receptor on B cells that have not been exposed to antigens, and activates basophils and mast cells, resulting in the production of antimicrobial factors. IgG, expressed in four forms, provides the majority of antibody-based immunity against invading pathogens. IgM is expressed on the surface of B cells as a monomer, and in a secreted form as a pentamer. It eliminates pathogens during the early phases of humoral (B cell-mediated) immunity before there 5 are sufficient levels of IgG. IgG is often used in immunotherapy.

The term antibody is used in the broadest sense and specifically includes, for example, single monoclonal antibodies, antibody compositions with polyepitopic specificity, single chain antibodies, and antigen-binding fragments of antibodies. An antibody may include an immunoglobulin constant domain from any immunoglobulin, such as IgG1, IgG2, IgG3, or IgG4 subtypes, IgA (including IgA1 and IgA2), IgE, IgD or IgM.

A fluorescence light source provides an excitation wavelength to excite a fluorophore. A fluorescent light source can be used in connection with a photosensitive detector capable of detecting total fluorescence emitted by the excited fluorophore to generate an image. A fluorescence microscope can be configured to include a fluorescence light source and a photosensitive detector. Fluorescence microscopes are available in the art and are commercially available. A skilled artisan would be able to select a microscope with appropriate capabilities for the desired imaging and/or analysis.

Fluorescence microscopes are available in upright or inverted configurations, either of which are suitable for use with the provided methods. In an upright microscope configuration, the objective and photosensitive detector, e.g., camera, is disposed above the stage, pointing down. Exemplary upright fluorescent microscopes include, but are not limited to, Nikon Eclipse 80i Fluorescent Microscope. In an inverted microscope configuration, the light source is disposed above the stage pointing down, and the objective is disposed below the stage pointing up.

In some embodiments, a fluorescence microscope is an epifluorescence microscope, in which light of the appropriate excitation wavelength is passed through the objective lens onto the sample to be examined. In some such embodiments, fluorescence is emitted from the sample through the same objective lens through which the light initially passed, and is then detected via a photosensitive detector, e.g., a camera. In some instances, a dichroic beam splitter may be used to filter the emitted fluorescence by permitting fluorescence of a particular wavelength to pass through, while reflecting the remaining fluorescence, to increase the signal-to-noise ratio. In some embodiments, a fluorescence microscope is a confocal microscope. Confocal microscopes can be used, for example, to generate three dimensional structures from a series of optical section images. In some embodiments, a fluorescence microscope is a total internal reflection fluorescence microscope.

In some embodiments, the fluorescence microscope is configured to permit measurement of emission of fluorescence from two or more distinct fluorophore dyes at distinct wavelengths. For example, in some embodiments, the fluorescence microscope contains a filter arrangement that allows separation of the fluorescence emitted by the two or more distinct fluorophore dyes.

In some embodiments, the microscope is configured to permit measurement of multiple capture images of the same microfluidic device by moving the stage on which the microfluidic device is disposed. In some embodiments, the stage is a motorized stage. Motorized stages are known in the art and are commercially available. In some embodiments, the stage is configured to move one dimensionally, e.g., to move in the x-axis. In some embodiments, the stage is configured to move two dimensionally, e.g., to move in the x- and y-axes. In some embodiments, the stage is configured not to move in three dimensions, e.g., to not move in the z-axis. In some such embodiments, the focal plane of the tumor cell spheroids in the three-dimensional microfluidic device remains the same throughout the fluorescence detection.

In some embodiments, a three dimensional analysis of the tumor cell spheroids is performed. For example, in some embodiments, the stage is configured to move in three dimensions, e.g., moves in x-, y-, and z-axes. In such embodiments, images of multiple sections (e.g., focal planes) can be obtained to generate a Z stack using microscopes, photosensitive detectors, and software available in the art. For example, commercially available ProScan controller and TTL Breakout Box (Prior Scientific, Rockland, Mass.) can be used to control a CCD camera for Z-stack image acquisition.

The overall resolution of the fluorescence emission detection depends on the magnification of the objective lens through which the detectable signal passes, and/or the magnification of the photosensitive detection device, e.g., camera. In some embodiments, the magnification of the objective lens is at least 2×, at least 3×, at least 4×, at least 10×, at least 40×, at least 100×, or more. In some embodiments, the magnification of the photosensitive detection device, e.g., camera, is 0×. In some embodiments, the magnification of the photosensitive detection device, e.g., camera, is at least 2×, at least 3×, at least 4×, at least 100×, or more. In some embodiments, the overall resolution of the fluorescence detection is at least 2×, at least 3×, at least 4×, at least 10×, at least 40×, at least 100×, at least 400×, at least 1000×, or more. In some embodiments, the resolution at which the fluorescence is detected is such that the entire field of the three dimensional device containing the tumor cell spheroids can be imaged without adjusting the focal plane.

Images of the fluorescence emitted by the fluorophore dyes are detected and/or captured using a photosensitive detector. Photosensitive detectors capable of detecting total fluorescence are known in the art and commercially available. In some embodiments, a photosensitive detector is a camera or a photodiode. In some embodiments, the camera is a CCD camera. Exemplary cameras include, but are not limited to CoolSNAP CCD Camera (Roper Scientific). In some embodiments, the photodiode is an avalanche photodiode.

Images can be acquired by the photosensitive detector and analyzed, e.g., using commercially available software. Exemplary image capture and analysis software includes, but is not limited to NIS-Elements AR software package (Nikon). In some embodiments, multiple images of a microfluidic device are captured by the detector and stitched together. Images may be deconvoluted using available programs such as AutoQuant (Media Cybernetics).

The present invention is further illustrated by the following Examples, which in no way should be construed as further limiting. The entire contents of all of the references (including literature references, issued patents, published patent applications, and co pending patent applications) cited throughout this application are hereby expressly incorporated by reference.

EXAMPLES Example 1. Materials and Methods for Ex Vivo Profiling

Patient Samples.

A cohort of patients (Tables S1-1 and S1-2) treated at Massachusetts General Hospital and Dana-Farber Cancer Institute was assembled for PDOTS profiling and culture between August 2015 and August 2016. Informed consent was obtained from all subjects. Tumor samples were collected and analyzed according to Dana-Farber/Harvard Cancer Center IRB-approved protocols. These studies were conducted according to the Declaration of Helsinki and approved by the MGH and DFCI IRBs. De-identified archival matched plasma and tissue samples from the MGH Melanoma Tissue Bank were obtained from patients pre- or on-treatment with anti-PD-1 therapy as indicated. Mutational analysis performed on clinically validated next-generation sequencing (NGS) platforms at MGH and DFCI. Clinical benefit (CB) to PD-1 was defined as absence of disease, decrease in tumor volume (radiographic or clinical), or stable disease, whereas patients with no clinical benefit (NCB) included patients with mixed response, progression on treatment, and primary non-responders.

TABLE S1-1 ID Age/Sex Diagnosis Stage Mutational Status MGH-01 78/M Melanoma IV BRAF^(WT), (cutaneous) NRAS^(WT) MGH-02 69/M Melanoma IIIB N/A (cutaneous) MGH-03 49/M Melanoma IV N/A (cutaneous) MGH-04 (**) 28/M Melanoma IV BRAF^(V600E) (cutaneous) MGH-05 70/M Melanoma IV BRAF^(WT), (cutaneous) NRAS^(G13V) MGH-06 78/M Melanoma IV BRAF^(WT), (cutaneous) NRAS^(WT) MGH-07(**) 28/M Melanoma IV BRAF^(V600E) (cutaneous) MGH-08 80/M Melanoma IV BRAF^(V600K) (cutaneous) MGH-09 69/F Melanoma IV BRAF^(V600E) (cutaneous) MGH-10 74/F Melanoma IV KIT^(D816A) (mucosal) MGH-11 63/F Melanoma IV N/A (cutaneous) MGH-12 ( 

 ) 61/M Melanoma IV TP53 (cutaneous) MGH-13 65/F Thyroid cancer IV BRAF^(V600E) (papillary) MGH-14 ( 

 ) 61/M Melanoma IV TP53 (cutaneous) MGH-16 62/M Melanoma (sino- IV NRAS^(G12D) nasal) MGH-18 68/M Melanoma IV NRAS^(Q61R) (cutaneous) MGH-19 24/F Adreno-cortical II N/A carcinoma DFCI-01 73/F Melanoma III Not tested (cutaneous) DFCI-02 (#) 81/M Melanoma IV CDKN2A (Q50*) (cutaneous) DFCI-04 72/F Mesothelioma IV 9p del, polysomy 22 DFCI-06 42/F Merkel cell IV BRCA2 (F439V) carcinoma DFCI-07 58/M NSCLC/lung IV KRAS/ LKB1 adeno-carcinoma DFCI-09 45/M Pancreatic IIB KRAS^(G12D), TP53 adenocarcinoma DFCI-10 ({circumflex over ( )}) 55/M Thyroid cancer IV TP53, MSH2, (Hurthle cell) PTEN DFCI-12 58/F Head/neck IV Unknown squamous cell carcinoma DFCI-13 (*) 76/M Thyroid cancer IV Unknown (papillary) DFCI-15 75/F Thyroid cancer IV BRAF^(V600E) (papillary) DFCI-16 (*) 76/M Thyroid cancer IV Unknown (papillary) DFCI-17 (#) 81/M Melanoma IV CDKN2A (Q50*) (cutaneous) DFCI-18 (*) 76/M Thyroid cancer IV Unknown (papillary) DFCI-19 67/M Pancreatic IIA Unknown adenocarcinoma DFCI-20 51/M Thyroid cancer IV None identified (papillary) DFCI-21 (*) 76/M Thyroid cancer IV Unknown (papillary) DFCI-22 (*) 76/M Thyroid cancer IV Unknown (papillary) DFCI-24 79/M Small cell lung IV Unknown cancer DFCI-25 68/M Melanoma IV NRAS^(Q61K), (cutaneous) CDKN2A (Q50*) DFCI-27 72/M Melanoma IV BRAF^(WT) (cutaneous) DFCI-29 ({circumflex over ( )}) 55/M Thyroid cancer IV TP53, MSH2, (Hurthle cell) PTEN DFCI-30 52/M Merkel cell IV Unknown carcinoma DFCI-31 67/M Merkel cell IV Unknown carcinoma DFCI-32 89/M Merkel cell IIIb Unknown carcinoma DFCI-33 49/M Thyroid cancer IV Unknown (differentiated) (*) DFCI-13, 16, 18, 21, 22 represent serial pleural effusion samples from same patient. (**) MGH-04 and MGH-07 are serial biopsies from the same patient. (#) DFCI-02 and -17 are samples from same patient. ({circumflex over ( )}) DFCI-10 and DFCI-29 are samples from the same patient. ( 

 ) MGH-12 and MGH-14 are serial samples from a patient with a brain metastasis requiring resection and subsequent re-resection.

TABLE S1-2 Therapy at Prior Time of Subsequent ID Therapy Biopsy Site Therapy Response to Status MGH-01 None None subcutaneous None N/A Deceased; never treated MGH-02 None None lymph node None N/A Alive; NED MGH-03 None None lymph node BRAFi + N/A Deceased; MEKi → progression αPD-1 + αCTLA-4 MGH-04 None None subcutaneous αPD-1 + N/A Alive; (**) αCTLA-4→ ongoing αPD-1 response maintenance MGH-05 αCTLA-4→ None subcutaneous None Progression Deceased; αPD-1→ progression clinical trial MGH-06 αPD-1 αPD-1 lymph node αPD-1 Mixed Alive; (irAE) → ongoing αCTLA-4 response MGH-07 αPD-1 + αPD-1 + Subcutaneous αPD-1 Response Alive; (**) αCTLA-4 αCTLA-4 ongoing response MGH-08 αPD-1+ αPD-1 Subcutaneous αCTLA-4→ Mixed Alive; BRAFi + Response ongoing MEKi response to BRAFi + MEKi MGH-09 αPD-1 → None Subcutaneous BRAFi + Response Alive; irAE MEKi (SD x 4-5 ongoing mo) PD off- response to therapy BRAFi + MEKi MGH-10 Chemo- None Small bowel None Response Alive; therapy, (partial)- NED radiation, held for surgery → irAE αCTLA-4→ αPD-1 MGH-11 BRAFi/ None Lymph node αPD-1 Response Alive; MEKi ongoing treatment MGH-12 αCTLA-4 αPD-1 Brain αPD-1 Mixed Alive; (□) (PD) → metastasis Response mixed αPD-1 (MR) response MGH-13 Radioactive None Subcutaneous Radiation N/A Alive; iodine awaiting further therapy MGH-14 αPD-1 αPD-1 Brain αPD-1 + Mixed Alive; (□) metastasis radiation Response stable disease MGH-16 Anti-PD-L1 + None Subcutaneous None Progression Deceased MEKi (PD) → high-dose IL-2 (AE) → αCTLA-4 (PD) → αPD-1(MR→ PD) → SIRT (liver metastases) → pan-RAFi (PD) MGH-18 Radiation → αPD-1 Subcutaneous αPD-1 Progression Alive; anti-PD-1 + (slow) slowly anti-KIR progressive (irAE) → disease αCTLA-4 (PD) →pan- RAFi (PD)→ αPD-1 + radiation MGH-19 None None Primary None N/A Alive DFCI-01 None Unknown Lymph node N/A Unknown Unknown DFCI-02 αCTLA-4, αPD-1 Subcutaneous αPD-1 Progression Deceased (#) αPD-1 DFCI-04 None Unknown Primary None N/A Deceased (partial pleurectomy) DFCI-06 None None Subcutaneous None N/A Deceased DFCI-07 Chemotherapy None Peritoneal None Progression Deceased (PD) → αPD 1 fluid DFCI-09 None None Pancreas None N/A Alive; (Whipple) recurrent disease DFCI-10 None None Subcutaneous lenvatinib N/A Alive ({circumflex over ( )}) DFCI-12 Cisplatin None Pleural biopsy αPD-1 Progression Deceased (VATS) DFCI-13 MLN-0128 MLN-0128 Pleural effusion MLN-0128 Progression Deceased (*) DFCI-15 MLN-0128 MLN-0128 Pleural effusion None N/A Deceased DFCI-16 MLN-0128 None Pleural effusion nivolumab N/A Deceased (*) DFCI-17 RTA 408 + RTA 408 + Subcutaneous N/A Progression Alive; (#) αCTLA-4 αCTLA-4 Progressive Disease DFCI-18 MLN-0128 None Pleural effusion nivolumab Progression Deceased (*) DFCI-19 FOLFIRINO None Pancreas 5-FU N/A Alive X → (Whipple) (NED) capecitabine + radiation DFCI-20 lenvatinib lenvatinib Pleural effusion MLN-0128 N/A Progressive Disease DFCI-21 αPD-1 αPD-1 Pleural effusion αPD-1 Progression Deceased (*) DFCI-22 αPD-1 αPD-1 Pleural effusion αPD-1 Progression Deceased (*) DFCI-24 cisplatin- αPD-1 Pleural effusion None Progression Deceased etoposide → αPD-1 DFCI-25 αCTLA- None Lymph node N/A Response Alive; 4 + αPD-1→ (held for irAE) awaiting αPD-1 further maintenance → therapy irAE DFCI-27 αPD-1 αPD-1 Subcutaneous αPD-1 Mixed Alive; Response on treatment DFCI-29 Lenvatinib → everolimus Subcutaneous everolimus N/A Alive ({circumflex over ( )}) MLN-0128 → everolimus DFCI-30 carboplatin- None Lymph node αPD-1 Response Alive; etoposide, on radiation treatment (recurrence) DFCI-31 carboplatin- None Subcutaneous αPD-1 Stable Alive; etoposide Disease on treatment DFCI-32 None None Primary Radiation N/A Alive; on treatment DFCI-33 Radioactive None Pleural effusion lenvatinib N/A Alive; iodine on treatment (*)DFCI-13, 16, 18, 21, 22 represent serial pleural effusion samples from same patient. (**) MGH-04 and MGH-07 are serial biopsies from the same patient. (#) DFCI-02 and -17 are samples from same patient. ({circumflex over ( )}) DFCI-10 and DFCI-29 are samples from the same patient. (□) MGH-12 and MGFI-14 are serial samples from a patient with a brain metastasis requiring resection and subsequent re-resection. AE = adverse event. irAE = immune-related adverse event. MR = mixed response. PD = progressive disease Syngeneic Murine Models.

All animal experiments were performed in compliance with established ethical regulations and were approved by the Dana-Farber Animal Care and Use Committee. MC38 murine colon adenocarcinoma cells were generously provided by Dr. Gordon Freeman (DFCI) received under an MTA from Dr. Jeffrey Schlom of NCI (Bethesda, Md.). B16F10 melanoma cells, CT26 colon carcinoma cells, and EMT6 breast mammary carcinoma cells were obtained from ATCC. Cells were expanded, tested free for mycoplasma and mouse pathogens. Thawed cells were cultured for up to three passages in DMEM (MC38, B16F10) or RPMI 1640 (CT26) supplemented with 10% heat-inactivated FBS at 37° C. in a humidified incubator maintained at 5% CO₂. Cell counts were performed prior to implantation by both hemocytometer & Invitrogen Countess Cell Counter. MC38 colon carcinoma cells, CT26 colon carcinoma cells, and B16F10 melanoma cells (5×10⁵ cells/mouse in 100 μL), re-suspended in sterile PBS (Ca⁺, Mg⁺ free), were injected into 8 week old female C57BL/6 albino mice or Balb/c (Jackson) and tumors were collected 2-3 weeks post-implantation or on reaching 2000 mm³ in size (or if there were any humane reason, including decreased BW>15% for 1 week or moribund) and MDOTS were prepared as described below. Implantation of CT26 colon carcinoma cells was performed using BALB/c mice in identical fashion. For in vivo treatment studies, mice were randomized (using the deterministic method) and then injected with 10 mg/kg isotype control IgG (clone 2A3, BioXCell) or rat-anti-mouse PD-1 (clone RMP1-14, BioXCell) every 3 days×8 doses and tumor volume was measured as shown. Investigators were not blinded to treatment groups. Tumor volume (TV) was monitored on a weekly basis after the initial tumor volume is about 100 mm³. TV was measured twice weekly during the exponential tumor growth phase, and body weight was monitored on a weekly basis after implantation.

Spheroid Preparation and Microfluidic Culture.

Fresh tumor specimens (murine and human patients) were received in media (DMEM) on ice and minced in a 10 cm dish (on ice) using sterile forceps and scalpel. Minced tumor was resuspended in DMEM (4.5 mM glucose, 100 mM sodium pyruvate, 1:100 penicillin-streptomycin) (Corning CellGro, Manassas, Va.)+10% FBS (Gemini Bio-Products, West Sacramento, Calif.), 100 U/mL collagenase type IV (Life Technologies, Carlsbad, Calif.), and 15 mM HEPES (Life Technologies, Carlsbad, Calif.), except for CT26 tumors that were prepared in RPMI. Samples were pelleted and resuspended in 10-20 mL media. Red blood cells were removed from visibly bloody samples using RBC Lysis Buffer (Boston Bio-Products, Ashland, Mass.). Samples were pelleted and then resuspended in fresh DMEM+10% FBS and strained over 100 μm filter and 40 μm filters to generate S1 (>100 μm), S2 (40-100 μm), and S3 (<40 μm) spheroid fractions, which were subsequently maintained in ultra low-attachment tissue culture plates. S2 fractions were used for ex vivo culture. An aliquot of the S2 fraction was pelleted and resuspended in type I rat tail collagen (Corning, Corning, N.Y.) at a concentration of 2.5 mg/mL following addition of 10×PBS with phenol red with pH adjusted using NaOH (pH 7.0-7.5 confirmed using PANPEHA Whatman paper (Sigma-Aldrich, St. Louis, Mo.)). The spheroid-collagen mixture was then injected into the center gel region of the 3D microfluidic culture device. Collagen hydrogels containing PDOTS/MDOTS were hydrated with media with or without indicated therapeutic monoclonal antibodies after 30 minutes at 37° C. MDOTS were treated with isotype control IgG (10 μg/mL, clone 2A3) or anti-PD-1 (0.1, 1.0, 10 μg/mL, clone RMP1-14). Monoclonal rat-anti-mouse-CCL2 (5 μg/mL, clone 123616, R&D Systems) was used for CCL2 neutralization in MDOTS. PDOTS were treated with anti-PD-1 (pembrolizumab, 250 μg/mL), anti-CTLA-4 (ipilimumab, 50 μg/mL), or combination (250 μg/mL pembrolizumab+50 μg/mL ipilimumab). Doses were selected (1:100 dilutions of stock concentrations used clinically) to correspond to reported peak plasma concentrations of each drug following administration of 10 mg/kg (FDA CDER application). In select experiments, PDOTS were treated with InVivoMAb human IgG isotype control (BioXCell). For spheroid cultures lacking immune cells, MC38 or CT26 cells (1×10⁶) were seeded in low attachment conditions for 24 hours and were filtered (as above). The S2 fraction was pelleted and resuspended in collagen (as above) prior to microfluidic culture.

Flow Cytometric Immune Profiling of Murine Tumors and MDOTS.

Tumors from MC38 and B16F10 syngeneic murine models were procured as described above. Cells were incubated for 20 minutes in the dark at room temperature using the Zombie NIR Fixable Viability Kit (Biolegend, 423105) at a dilution of 1:500 in PBS. FcR were blocked by incubation with the anti-mouse CD16/CD32 clone 2.4G2 blocking Ab (Fisher Scientific) for 15 minutes at 4° C. at a 1:100 dilution in flow cytometry staining buffer (PBS+5% FBS). Cell surface staining was performed by incubation for 20 minutes at 4° C. using the following Abs diluted in flow cytometry staining buffer (total staining volume of 100 uL): Lymphocyte Staining Panel—CD45 AF488 (BioLegend 103122), CD25 PE (BioLegend 101904), CD19 PE-Dazzle (115554), CD49b PE-Cy7 (BioLegend, 108922), CD3 BV421 (BioLegend, 100228), CD8 BV510 (BioLegend 100752), CD4 BV786 (Fisher Scientific #BDB563331); Myeloid Staining Panel—F4/80 AF488 (BioLegend #123120), MHCII PE (BioLegend #107608), CD11c BV421 (BioLegend #117330), Ly6G BV510 (BioLegend #127633), CD11b BV650 (BioLegend #101239), Ly6C BV711 (BioLegend #128037), CD45 BV786 (Fisher Scientific #BDB564225), CD19 APC-Cy7 (BioLegend #115530), and CD49b APC-Cy7 (BioLegend #108920) were included with the myeloid staining panel to be used as a dump channel along with the dead cells as determined by the Zombie NIR viability stain. After cell surface staining, cells were fixed by incubating in 200 μL IC Fixation Buffer (eBioscience #00-8222-49) for 10 minutes at room temperature. Cells were washed and resuspended in flow cytometry staining buffer and read the following day on a BD LSR Fortessa flow cytometer. Data were analyzed using FlowJo software version 10.0.8.

Flow Cytometric Immune Profiling of PDOTS and Human Tumor Samples.

Cells were incubated with Live/Dead Fixable Yellow Dead Cell Stain Kit (Life Technologies, Carlsbad, Calif.) for 8 minutes in the dark at room temperature or Live/Dead Fixable Zombie NIR™ (Biolegend, San Diego, Calif.) for 5 minutes in the dark at room temperature in FACS buffer (PBS+2% FBS) at a ratio of 250 μL L/D 1× dilution per 100 mg of original sample weight. Surface marker and intracellular staining were performed according to the manufacturer's protocol (eBioscience, San Diego, Calif.). FcR were blocked prior to surface antibody staining using Human FcR Blocking Reagent (Miltenyi, San Diego, Calif.). Cells were fixed in 1% PBS+2% FBS and washed prior to analysis on a BD LSRFortessa with FACSDiva software (BD Biosciences, San Jose, Calif.). Data were analyzed using FlowJo (Ashland, Oreg.) software version 10.0.8. Cell viability was determined by negative live/dead staining. Antibodies were specific for the following human markers: CD3 (HIT3a; UCHT1), CD8 (RPA-T8), CD14 (M5E2; MphiP9), CD45 (HI30), CD56 (B159), CCR7 (150503), EpCAM (EBA-1), HLA-DR (G46-6), PD-1 (EH12.1), and IgG1 isotype control (MOPC-21) from BD Biosciences (San Jose, Calif.); CD3 (UCHT1), CD4 (RPA-T4), CD14 (M5E2), CD15 (W6D3), CD16 (3G8), CD19 (HIB19), CD25 (BC96), CD33 (WM53), CD38 (HIT2), CD40L (24-31), CD45 (HI30), CD45RA (HI100), CD45RO (UCHL1), CD56 (HCD56; 5.1H11), CD66b (G10F5), CD69 (FN50), CD123 (6H6), CD163 (GHI/61), CTLA-4 (L3D10), CXCR5 (J252D4), EpCAM (9C4), Ki-67 (Ki-67), PD-1 (EH12.2H7), PD-L1 (29E.2A3), PD-L2 (24F.10C12), TIM-3 (F38-2E2), IgG2a isotype control (MOPC-173), IgG2b isotype control (MPC-11), and IgG1 isotype control (MOPC-21) from BioLegend (San Diego, Calif.); Pan-cytokeratin (C11) and PD-L1 (E1L3N) from Cell Signaling Technologies (Danvers, Mass.); CD45 (2D1), FOXP3 (236A/E7), and IL-10 (236A/E7) from Affymetrix/eBioscience (San Diego, Calif.). Four-way flow sorting of immune cells (CD45+), tumor cells (CD45−CD31−CD90−), cancer-associated fibroblasts (CD45−CD31−CD90+), and endothelial cells (CD45−CD31+CD144+) was conducted on a BD Aria II SORP with gates set using single stain controls and manual compensation using the following antibodies: CD31-APC (Biolegend, 303115), CD45-BV711 Biolegend, 304050), CD90-PE/Cy7 (Biolegend, 328123), and CD144-PE (Biolegend, 348505). Cells were sorted into cold PBS and stored on ice before mRNA extraction using established techniques.

Microfluidic Device Design and Fabrication.

Microfluidic device design and fabrication was performed according to methods known in the art (e.g., Aref, A. R. et al., Integr. Biol. (Camb.) (2013), the content of which is incorporated herein by reference in entirety), with modifications of device dimensions to accommodate larger volumes of media. MDOTS were also evaluated using DAX-1 3D cell culture chip (AIM Biotech, Singapore), for select studies.

Live/Dead Staining.

Dual labeling was performed by loading microfluidic device with Nexcelom ViaStain™ AO/PI Staining Solution (Nexcelom, CS2-0106). Following incubation with the dyes (20 minutes at room temperature in the dark), images were captured on a Nikon Eclipse 80i fluorescence microscope equipped with Z-stack (Prior) and CoolSNAP CCD camera (Roper Scientific). Image capture and analysis was performed using NIS-Elements AR software package. Image deconvolution was done using AutoQuant Module. Whole device images were achieved by stitching in multiple captures. Live and dead cell quantitation was performed by measuring total cell area of each dye. Three different laboratories verified immune-mediated cell death of MC38 MDOTS following PD-1 blockade. To inhibit CD8+ T cell cytotoxicity, CT26 MDOTS were treated with 10 μg/mL anti-CD8a Ab (clone 53-6.72, BioXCell). Intertumoral and intratumoral heterogeneity experiments were performed using CT26 allografts as described above. MDOTS were prepared using separate pieces of a larger tumor alongside MDOTS prepared from a smaller allograft. MDOTS were processed, treated, and profiled as described above. Immunofluorescence for CD8+ T cells was performed as described below.

Immunofluorescence and Time-Lapse Imaging.

For immunofluorescence studies, PDOTS and MDOTS were washed with PBS and blocked with FcR blocking reagent (PDOTS—Miltenyi, Cambridge, Mass., MDOTS—BioLegend, San Diego, Calif.) for 30 minutes at room temperature. Directly conjugated antibodies for PDOTS were CD326 EpCAM-PE (clone 9C4), CD45-AlexaFluor-488 (HI30), CD8a-AlexaFluor488 (RPA-T8); for MDOTS—CD45-AlexaFluor488 or 647 (30-F11), CD8a-PE (53-6.7) (BioLegend, San Diego, Calif.). Antibodies were diluted 1:50 in 10 ug/mL solution of Hoechst 33342 (Thermo Fisher Scientific, Waltham, Mass.) in PBS and loaded into microfluidic devices for 1-hour incubation at room temp in the dark. Spheroids were washed twice with PBS with 0.1% Tween20 followed by PBS. For viability assessment, microfluidic devices were loaded with 1:1000 solution of calcein AM (Thermo Fisher Scientific, Waltham, Mass.) in PBS. Images were captured on a Nikon Eclipse 80i fluorescence microscope equipped with Z-stack (Prior) and CoolSNAP CCD camera (Roper Scientific). Image capture and analysis was performed using NIS-Elements AR software package. Brightfield time-lapse images were captured with a 10×NA 0.3 objective and cooled CCD camera (Orca R2, Hamamatsu) in a humidified, temperature-controlled chamber. Illumination was with a CoolLED pe-100 white light LED. Time lapse imaging of several fields of view over time was controlled by NISElements software of a Prior motorized stage along with the LED and camera.

Cytokine Profiling.

Two multiplex assays were performed utilizing a bead-based immunoassay approach, the Bio-Plex Pro™ Human Cytokine 40-plex Assay (Cat #171AK99MR2) and Bio-Plex Pro™ Mouse Cytokine Panel 1, 23-plex (Cat #M60009RDPD) on a Bio-plex 200 system (Cat #171000201). MDOT/PDOT conditioned media concentration levels [pg/mL] of each protein were derived from 5-parameter curve fitting models. Fold changes relative to the MDOT/PDOT control were calculated and plotted as log 2FC. Lower and upper limits of quantitation (LLOQ/ULOQ) were imputed from standard curves for cytokines above or below detection. Conditioned media from PDOTS were assayed neat and plasma was diluted 1:4.

Tertiary Lymphoid Structure Evaluation.

Fifty-two sections stained with hematoxylin & eosin (H&E) of melanoma pre- and on-therapy with anti-PD-1 were evaluated independently by two dermatopathologists for the presence of tertiary lymphoid structures (TLS) at the periphery of these tumors. These are characterized by prominent lymphocytic infiltrate, sometimes with germinal center formation and with associated high endothelial venules, as shown in FIG. 10A.

RNA-seq.

Freshly isolated patient tumor samples (from patients consented to DF/HCC protocol 11-181) were snap frozen in liquid nitrogen and RNA was collected using the Qiagen RNeasy Mini kit. RNA libraries were prepared from 250 ng RNA per sample using standard Illumina protocols. RNA sequencing was performed at the Broad Institute (Illumina HiSeq2000) and the Wistar Institute (Illumina NextSeq 500). RNA samples were ribo-zero treated and then subjected to library prep using Epicentre's ScriptSeq Complete Gold kit. Quality check was done on the Bioanalyzer using the High Sensitivity DNA kit and quantification was carried out using KAPA Quantification kit. Raw RNA-Seq data (BAM files) read counts were summarized by featureCounts with parameters that only paired-ended, not chimeric and well mapped (mapping quality>/=20) reads are counted. Then normalization was applied to eliminate bias from sequencing depths and gene lengths by edgeR, thus RPKMs (Reads Per Kilobase of transcript per Million mapped reads).

Quantitative Real-Time PCR.

Analysis of expression levels of CCL19 and CXCL13 by quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed using tissue samples obtained from patients with metastatic melanoma. Samples were selected from patients treated with anti-PD-1 therapy with available tissue pre- and on-treatment. All patients provided written consent to DF/HCC protocol 11-181 (Melanoma Tissue and Blood Collection). Tissue samples were snap frozen in liquid nitrogen and processed to yield RNA, which was stored at −80° C. after extraction. Normal lymph node tissue was used as a positive control for expression of CCL19 and CXCL13. Primers were designed for CXCL13 (Fwd: 5′-GAGGCAGATGGAACTTGAGC-3′ (SEQ ID NO: 1), Rev: 5′-CTGGGGATCTTCGAATGCTA-3′ (SEQ ID NO: 2)) and CCL19 (Fwd: 5′-CCAACTCTGAGTGGCACCAA-3′ (SEQ ID NO: 3), Rev: 5′-TGAACACTACAGCAGGCACC-3′ (SEQ ID NO: 4)), Total RNA was extracted via the QIAGEN RNeasy Mini Kit after being ground with the QIAGEN TissueRuptor. The extraction process was automated via the QIAGEN QIAcube. RNA was stored in 1.5 mL RNAse-free EP tubes and then quantified using the QIAGEN Qubit. cDNA was reverse-transcribed from RNA using the Invitrogen Superscript VILO kit run on an Applied Biosystems 2720 Thermo Cycler and then stored in 1.5 mL tubes in a −40° C. freezer until later use. For qPCR the samples were run in triplicate on a Roche LightCycler 96 using Bio-Rad's SsoAdvanced Universal SYBR Green Supermix in a total volume of 20 μL per well. β-tubulin (Fwd: 5′-CGCAGAAGAGGAGGAGGATT-3′ (SEQ ID NO: 5), Rev: 5′-GAGGAAAGGGGCAGTTGAGT-3′ (SEQ ID NO: 6)) were employed to normalize the expression of target genes. Four runs were performed. RT-PCR was performed in triplicate and values averaged. Effect of PD-1 blockade depicted as log 2 fold change in CCL19 or CXCL13 expression (normalized to β-tubulin) from on-treatment samples relative to pre-treatment samples. For analysis of CCL19/CXCL13 expression in sorted cell populations (FIG. 10H), qRT-PCR was performed according to methods known in the art (e.g., Zhu, Z. et al. Cancer Discov. (2014), the content of which is incorporated herein by reference in entirety) using the following primers: and CXCL13 (Fwd: 5′-CTCTGCTTCTCATGCTGCTG-3′ (SEQ ID NO: 7), Rev: 5-TGAGGGTCCACACACACAAT-3′ (SEQ ID NO: 8)) and CCL19 (Fwd: 5′-ATCCCTGGGTACATCGTGAG-3′ (SEQ ID NO: 9), Rev: 5′-GCTTCATCTTGGCTGAGGTC-3′ (SEQ ID NO: 10)), using 36B4 (Fwd: 5′-CAGATTGGCTACCCAACTGTT-3′ (SEQ ID NO: 11), Rev: 5′-GGAAGGTGTAATCCGTCTCCAC-3′ (SEQ ID NO: 12)) to normalize gene expression.

Immunohistochemistry.

Immunohistochemistry staining was performed on 4 μm formalin-fixed paraffin-embedded sections. All procedures were done on the automated Ventana Discovery Ultra staining system. Sections were first deparaffinized using EZ prep solution and antigen retrieval was achieved using Cell Conditioning solution 1. Sections were blocked with Discovery Inhibitor (all from Ventana). Sections were incubated with primary antibodies for 16 minutes for population markers and 12 hours for CXCL13 and CCL19, then washed and incubated with OmniMap anti-Mouse or anti-Rabbit conjugated with horseradish peroxidase (HRP) (Ventana, cat #760-4310 and 760-4311) for an additional 16 minutes. Discovery Purple or OmiMAP DAB chromogen kits (cat #760-229 or 760-159) was then applied to generate a color reaction. Slides were then counterstained with hematoxylin II followed by bluing reagent (Ventana, cat #790-2208 and cat #760-2037). Primary antibodies used for staining were: anti-CCL19 (RD Systems, cat #MAB361-100; 1:200) and anti-CXCL13 (Abcam, cat #ab112521; 1:150), CD31 (Cell Marque, cat #131M-94; 1:500); αSMA (Abcam, cat #ab5694; 1:400).

Source Data.

Data for differential CCL19 and CXCL13 gene expression analysis were obtained from published reports (e.g., Hugo, W. et al. Cell (2016), Chen, P. L. et al. Cancer Discov. (2016), Van Allen, E. M. et al. Science (2015), Cancer Genome Atlas, N. Cell (2015), the contents of each of which are incorporated herein by reference in entirety). For data from Ilugo et al. and Van Allen et al., transcriptome sequencing data were aligned using TopHat and normalized gene expression, presented as transcripts per million (TPM), was quantified using DESeq2 (e.g., see Kim, D. et al. Genome Biol. (2013), and Love, M. I. et al. Genome Biol. (2014), the contents of each of which are incorporated herein by reference in entirety) (Table S3). NanoString source data (Chen et al.) for PD-1 responders (n=4) and non-responders (n=8) were compared (on-PD-1/pre-PD-1) and expressed as log-2 fold change. For TCGA analysis, raw RNA-Seq data (BAM files) of TCGA SKCM samples was downloaded from Genomic Data Commons and read counts were summarized (featureCounts) and normalized using edgeR, to generate RPKMs. CCL19 and CXCL13, samples were separated into two groups by kmeans clustering of RPKM values: high group and low group, value of center of each group was used to label high or low. The survival curves were constructed according to Kaplan-Meier method on these two groups (high; n=206 and low; n=257) and survival was compared between groups using the logrank (Mantel-Cox) test (α=0.05). Four-way grouping was performed using median cutoff to define high and low expression. Single sample GSEA (ssGSEA) was performed using immune cell signatures according to methods known in the art (e.g., Bindea, G. et al. Immunity (2013), the content of which is incorporated herein by reference in entirety).

Synthesis of Compound 1, 5-(4-((4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)amino)-1,3,5-triazin-2-yl)-2-((tetrahydro-2H-pyran-4-yl)oxy)benzonitrile

Step 1.

To a solution of 2,4-dichloro-1,3,5-triazine (9.5 g, 63 mmol) in N,N-dimethylformamide (150 mL) at 0° C. (flushed with argon balloon) was added a solution of 4-(4-(oxetan-3-yl)piperazin-1-yl)aniline (14.1 g, 60.2 mmol) in N,N-dimethylformamide (100 mL) over 5 minutes via cannula and stirred in an ice-bath for 1 hour. A solution of 40% Methanol/CH₂Cl₂ (200 mL) was added to the reaction mixture and stirred at room temperature. After 1 hour, the solid formed were filtered and washed twice with diethyl ether. Solids were collected to provide the first lot of product. To the filtrate, diethyl ether (200 mL) was added and stirred overnight at room temperature. The solids were separated by filtration to provide a second lot of product. Both lots were combined to provide a total yield of 20 g (91%) of 4-chloro-N-(4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)-1,3,5-triazin-2-amine which was used without purification. LCMS-ESI⁺ (m/z): calculated for C₁₆H₁₉ClN₆O: 346.1; found: 347.1 (M+H).

Step 2.

To a mixture of 4-chloro-N-(4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)-1,3,5-triazin-2-amine (4.6 g, 13.2 mmol), 2-fluoro-5-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)benzonitrile (3.5 g, 14.5 mmol), Pd(dppf)Cl₂CH₂Cl₂ (1.2 g, 1.6 mmol) and potassium carbonate (3.6 g, 26.4 mmol) under argon was added a mixture of de-gassed solvents (1,2-dimethoxyethane (53 mL)/water (27 mL)) and sonicated until all solids went into solution (˜5 minutes). The mixture was stirred under argon at 100° C. in a heating block for 1 hour. After cooling to room temperature, water (200 mL) was poured into the reaction mixture and the solids were filtered off and washed with diethyl ether (100 mL). The resulting dark brown solids were suspended in Acetonitrile (20 mL) and stirred at reflux (˜2 minutes) and then stirred at room temperature for 2 hours. To this suspension di-ethyl ether (20 mL) was added and the mixture was stirred at room temperature overnight. Solids were taken by filtration to yield crude dark brown product. In 1 g batches, the crude product was suspended in Dichloromethane (150 mL) in a separatory funnel. To the suspension Trifluoroacetic acid was added until all solids had gone into solution. Water was added (150 mL) and mixture was shaken vigorously until black precipitates appeared. The black solids were filtered off. To the filtrate, a saturated aqueous solution of NaHCO₃ was added slowly to fully neutralize the mixture. No solids precipitated during this process. The organic phase was dried over MgSO₄ and evaporated under reduced pressure to yield a bright yellow material (Total yield 3.1 g, 55% yield). LCMS-ESI⁺ (m/z): calculated for C₂₃H₂₂FN₇O: 431.1; found: 432.2 (M+H).

Step 3.

To a solution of Tetrahydro-2H-pyran-4-ol (4.7 mL, 49 mmol) in THF (200 mL) at 0° C., Potassium t-butoxide (3.8 g, 51 mmol) was added and the reaction mixture was allowed to warm to room temperature. After 30 minutes, solid 2-fluoro-5-[4-([4-[4-(oxetan-3-yl)piperazin-1-yl]phenyl]amino)-1,3,5-triazin-2-yl]benzonitrile (10 g, 23.2 mmol) was added and stirred overnight at 60° C. The reaction mixture was then cooled to 0° C. with a water/ice bath and slowly diluted with water (1.2 L) over 30 minutes and stirred at room temperature for 45 minutes. The solids formed were filtered and dried to give 5-(4-((4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)amino)-1,3,5-triazin-2-yl)-2-((tetrahydro-2H-pyran-4-yl)oxy)benzonitrile as a yellow solid (10.6 g, 90% yield) LCMS-ESI⁺ (m/z): calculated for C₂₈H₃₁N₇O₃: 513.3; found: 514.5 (M+H) 1H NMR (400 MHz, DMSO-d6) δ 10.23 (d, J=19.4 Hz, 1H), 8.80 (s, 1H), 8.74-8.50 (m, 2H), 7.68 (br, 2H), 7.60 (d, J=9.0 Hz, 1H), 7.11 (br, 2H), 4.99 (m, 1H), 4.91-4.74 (m, 4H), 4.52 (m, 1H), 3.91 (m, 2H), 3.59 (ddd, J=11.6, 8.5, 3.0 Hz, 2H), 3.80-3.30 (m, 4H), 3.30-2.90 (m, 4H), 2.09 (m, 2H), 1.87-1.64 (m, 2H).

In Vitro Characterization of Compound 1.

Biochemical single point inhibition and IC₅₀ concentrations for TBK1, IKKε (IKBKE), and off-target kinases were determined at ThermoFisher Scientific using SelectScreen Kinase Profiling Services (Madison, Wis., USA) (Tables S4A and S4B-1-7). To determine cellular potency, the human colorectal cancer carcinoma cell line HCT116 (ATCC, Manassas, Va.) was maintained in T175 flasks in complete RPMI medium; RPMI 1640 supplemented with 10% FBS, 1× Penicillin-Streptomycin solution and 1×MEM (non-essential amino acids). HCT116 cells were grown to 90-95% confluency in T175 flasks containing complete RPMI medium and transfected in bulk using Lipofectamine 2000 (Invitrogen, Carlsbad, Calif.) with 70 μg of ISG54-luciferase reporter plasmid (Elim Biopharmaceuticals Inc., Hayward, Calif.). The reporter plasmid contains a luciferase gene expression cassette under the transcriptional regulation of the promoter of the human interferon stimulated gene 54 (ISG54). Transfection of the cells was allowed to take place for 6 hours, after which the cells were harvested by treatment with 0.25% trypsin EDTA (Corning Inc., Corning, N.Y.). Trypsinized cells were added to 384-well poly-d-lysine treated black clear bottom tissue culture assay plates (Greiner Bio-One GmbH, Kremsmünster, Austria) at a density of 20,000 cells/well in 80 μL of complete RPMI medium and incubated overnight. After 16-18 hours post-transfection, the assay plates were washed with PBS (Corning Inc., Corning, N.Y.), followed by addition of 80 μL/well of serum-free RPMI 1640 medium containing 1× Penicillin-Streptomycin solution, 1×MEM and 350 nL of DMSO or titrations of Compound 1. Compound 1 titrations were generated by 1.5-fold dilution steps in Iwo overlapping serial dilution series to generate a 40-point compound dose range. After incubation at 37° C. for 1 hour, the cells were stimulated with Poly(I:C) (InvivoGen, San Diego, Calif.) at a final concentration of 15 μg/mL in Optimem media (Life Technologies, Rockville, Md.). The assay plates were incubated for 5 hours at 37° C., followed by addition of One-Glo luciferase firefly reagent (Promega, Madison, Wis.) at 1:1 volume/well and luminescence was measured in an EnVision Multilabel Plate Reader (PerkinElmer, Santa Clara, Calif.). The EC₅₀ values were calculated from the fit of the dose-response curves to a four-parameter equation. All EC₅₀ values represent geometric mean values of a minimum of four determinations.

Interleukin-2 and Interferon Gamma Analysis.

Freshly isolated human CD4+ and CD8+ T cells were obtained from AllCells (Alameda, Calif., USA). Cells were spun down and resuspended in serum free Xvivo15 media (Lonza Walkersville, Inc., Chicago, Ill., USA) supplemented with 5 ng/mL IL-17 and incubated overnight at 37° C. Cells were plated on anti-CD3 coated plates (5 μg/mL OKT3, eBioscience, Dallas, Tex., USA, overnight) with 2 μg/mL anti-CD28 (eBioscience, Dallas, Tex., USA). Cells are treated in replicate plates with a dose-titration of Compound 1 for 24 hours for IL-2 and 96 hours for IFNγ. IL-2 and IFNγ in the supernatant were measured using single- or multi-plex immunoassay (Mesoscale Discovery, Rockville, Md., USA). Jurkat T cell leukemia cells (clone E61 obtained from ATCC) plated on anti-CD3 coated plates were treated with a dose titration of Compound 1 for 24 hours. IL-2 in the supernatant was measured as described above.

In Vivo Compound 1 Combination Treatments.

Combination studies were performed by vivoPharm (Hummelstown, Pa., USA). All procedures used in the performance of these studies were carried out in accordance with vivoPharm's Standard Operating Procedures, with particular reference to US_SOPvP_EF0314 “General Procedures for Efficacy Studies.” CT26 colon carcinoma cells (1×10⁶ cells/mouse in 100 μL, passage 2-3) were re-suspended in serum-free DMEM and implanted in the upper right flank of 11-12 week old female Balb/c mice (Charles River Laboratories). Mice were randomized into four groups of 10 using a matched pair distribution method based on tumor size for CT26. Treatment was initiated 12 days post-inoculation with mean tumor volume at start of dosing of 125.85 mm³. Vehicle or Compound 1 (40 mg/kg) was administered by oral gavage daily for 26 days and isotype control or a reverse chimera anti-PD-L1 cloned from literature reports (e.g., Deng, R. et al. MAbs (2016), the content of which is incorporated herein by reference in entirety) and placed into a mouse IgG1 framework (10 mg/kg) was administered every 5 days for a total of six doses. Investigators were not blinded to treatment groups. Mice bearing CT26 tumors with exceptional responses to combination therapy with αPD-L1 and Compound 1 were re-implanted with CT26 cells (1×10⁶, lower left flank) and EMT6 cells (0.5×10⁶, upper left flank) to evaluate development of immunologic memory. MB49 and MC38 in vivo combination studies performed under identical conditions in B6 mice. B16F10 tail vein injection studies were performed in accordance with methods known in the art (e.g., Zhang, J. et al. Cell Rep. (2016), the content of which is incorporated herein by reference in entirety). After tail vein injection (1×10⁵ cells in 100 μL), mice were treated with Vehicle or 40 mg/kg Compound 1 daily for 13 days±anti-PD-L1 (10 mg/kg) or isotype control on Days 0, 5, and 10. Mice were sacrificed on Day 13 and lung metastases were quantified (small<1 mm, medium>1 mm and ≤3 mm, large≥3 mm). No large lung metastases were detected.

Statistical Methods and Data Analysis.

All graphs depict mean±s.d. unless otherwise indicated. Graphs were generated and statistical analysis performed using GraphPad/Prism (v7.0) and R statistical package. Pearson correlation matrix using 21 cell surface markers for MDOTS were calculated with R across tumors and different sized spheroids. Unsupervised hierarchical clustering was performed using GenePattern.

Example 2. Ex Vivo Profiling of PD-1 Blockade Using Organotypic Tumor Spheroids

Existing patient-derived cancer models, including circulating tumor cells (CTCs), organoid cultures, and patient-derived xenografts (PDXs) can guide precision cancer therapy, but take weeks to months to generate and lack the native tumor immune microenvironment. Current approaches to study anti-tumor immune responses in patients are also limited by remote measurements in whole blood or plasma, or static assessment of biopsies. To overcome these challenges and model immune checkpoint blockade (ICB) ex vivo, a 3D microfluidic device was adapted to the short-term culture of murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). Following limited collagenase digestion of fresh tumor specimens, multicellular organotypic spheroids with autologous immune cells were isolated. MDOTS/PDOTS were analyzed by flow cytometry (FIG. 5) or loaded in collagen into the central channel of the device for exposure to anti-PD-1 or anti-CTLA-4 antibodies (FIG. 1A).

Using the MC38 and B16F10 immune competent syngeneic murine tumor models, lymphoid and myeloid immune cell composition of bulk tumor was compared with different spheroid populations (S1>100 μm; S2 40-100 μm; and S3<40 μm). Flow cytometric analysis revealed similar populations across all immune cell fractions examined (FIG. 1B, FIGS. 6A-6C, Tables S2-1 through S2-4). MDOTS (S2) from B16F10 demonstrated fewer CD45+ cells than MC38 and another model, CT26 (Extended Data FIG. 2d ), although immune sub-populations were relatively consistent across MC38, B16F10, and CT26 models (FIG. 6E). Since S2 MDOTS were optimally sized for culture in the microfluidic device, this fraction was utilized for subsequent studies.

A large panel of PDOTS (n=40) was immunophenotyped by flow cytometry, enriching for cancers responsive to PD-1 blockade (e.g., melanoma, Merkel cell carcinoma) (FIG. 1C, Tables 1A and 1B). A range of lymphoid (CD19+B cells, CD4+ and CD8+ T cells) and myeloid (CD15+ granulocytic, CD14+ monocytic lineages, CD123+ dendritic cells) populations were consistently detected in PDOTS (FIG. 1C). Variable surface expression of exhaustion markers (PD-1, CTLA-4, TIM-3) was detected on CD4+ and CD8+ T cells (FIG. 6F) and PD-1 ligands (PD-L1 and PD-L2) on myeloid populations, including dendritic cells, myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs) (FIG. 6G). A strong correlation of T-cell profiles was confirmed between PDOTS (S2) and S3 fractions, including antigen-experienced (CD45RO+) (FIG. 1D) and exhausted CD4 and CD8 T cells (FIG. 1E), and overall conservation of immunophenotype regardless of spheroid size (FIGS. 6H-6J). These data demonstrate that PDOTS retain autologous immune cells, including key tumor-infiltrating T lymphocyte populations.

3D microfluidic culture of MDOTS and PDOTS resulted in growth and expansion over time (FIG. 2A) as well as cytokine elaboration in conditioned medium (FIGS. 2B-2C). Tumor/immune cell intermixture in spheroids was further demonstrated by immunofluorescence microscopy (FIGS. 7A-7C). Dynamic cellular interactions were observed by live imaging, and survival of CD45+ immune cells ex vivo in the device was confirmed (FIG. 7D). Thus, short-term culture and cytokine profiling of PDOTS/MDOTS is feasible using this 3D microfluidic device.

MDOTS were exposed to ex vivo PD-1 blockade, starting with MC38 allografts that respond to anti-PD-1 treatment in vivo (FIGS. 2D-2E). MC38 MDOTS were treated with anti-PD-1 antibody (or isotype control) for 3 days or 6 days in the device (FIG. 2F). Dual labeling de-convolution fluorescence microscopy using acridine orange (AO, live cells) and propidium iodide (PI, dead cells) demonstrated >90% viability of MDOTS at the time of spheroid loading (Day 0) and over time in culture with control (FIG. 2G). Treatment with anti-PD-1 resulted in dose- and time-dependent killing of MC38 MDOTS (FIG. 2G, FIG. 2K, FIG. 7E), in contrast to cell line-derived MC38 spheroids lacking autologous immune/stromal cells (FIG. 2H). Modest killing was evident in the intermediately sensitive CT26 model (FIG. 2I), whereas MDOTS derived from the PD-1 resistant B16F10 model exhibited little cell death despite identical treatment (FIGS. 2J-2K). Anti-PD1 induced killing of CT26 MDOTS required CD8+ T cells (FIG. 7F), which varied between tumors of different size, but not between distinct regions from a single tumor (FIG. 7G). These data demonstrate the ability to recapitulate sensitivity and resistance to PD-1 blockade ex vivo using well-defined mouse models.

Responses to PD-1 blockade in PDOTS were evaluated. To perform systematic assessment of ex vivo ICB in PDOTS, acute cytokine production was used as a quantitative measure of early immune activation rather than ex vivo killing, which was more robust in MDOTS. Day 3 cytokine release from PDOTS (n=28)+PD-1 blockade was analyzed, and upregulation of CCL19 and CXCL13 was observed in the majority of samples (23/28) (FIG. 3A, FIG. 3D, FIGS. 8A-8C). CCL19/CXCL13 induction was not observed with isotype IgG control (FIG. 8D), and was comparatively minimal following CTLA-4 blockade (FIG. 4B, FIG. 4E). CCL19/CXCL13 generation was also preserved across a range of spheroid numbers (FIG. 8E) with little intra-assay variability (FIGS. 8F-8G). CCL19 correlated with CXCL13 across PDOTS samples, and required the microfluidic device for robust induction (FIGS. 8H-8I). CCL19/CXCL13 upregulation was also evident following dual PD-1+CTLA-4 blockade (FIG. 3C, FIG. 3F), and accompanied by induction of additional effector cytokines (e.g., IFN-γ, IL-2, and TNF-α) in select samples (FIG. 9).

In consonance with PDOTS profiling results, CCL19/CXCL13 mRNA expression increased in patients treated with PD-1 blockade (FIGS. 3G-3H, Tables S4A and Tables S4B-1 through S4B-7). Although fold induction of CCL19/CXCL13 did not clearly correlate with response (FIG. 10A), higher absolute levels of CCL19 and CXCL13, and their receptors (CCR7 and CXCR5), was evident in banked samples from melanoma patients with clinical benefit (CB) from checkpoint blockade (FIGS. 3I-3J, FIGS. 10B-10C). Pretreatment CCL19/CXCL13 mRNA expression levels alone failed to correlate with responsiveness to PD-1 or CTLA-4 blockade in melanoma RNAseq datasets (FIGS. 10D-10E). NanoString data from matched formalin-fixed and paraffin-embedded tissue or banked plasma was also insufficient to detect correlation with response (FIGS. 10F-10G).

As PD-1 blockade promotes immune cell infiltration in vivo, gene set enrichment analysis (GSEA) was performed using published immune signatures, which revealed enrichment of diverse immune cell populations in patients with CB to checkpoint blockade (FIG. 3K). To evaluate the clinical significance of CCL19/CXCL13, Cancer Genome Atlas melanoma (SKCM) data were analyzed. Improved patient survival was evident in melanoma specimens with higher expression of CCL19/CXCL13 (FIGS. 3L-3M; p<0.001). Evaluation of TCGA data for other cancers (e.g., bladder cancer, head and neck, and breast) revealed similar a pattern (FIG. 10H). Immune GSEA using melanoma TCGA data confirmed enrichment of diverse immune cell gene sets in melanoma patients with high levels of both CCL19 and CXCL13 (FIG. 3N), consistent with their established roles as chemoattractants.

CCL19/CXCL13 coordinate humoral and cell-mediated adaptive immunity in lymph nodes and tertiary lymphoid structures (TLS), and cancer-associated TLS have been associated with improved prognosis. Histologic review of melanoma biopsy specimens pre- and on-anti-PD1 only identified rare TLS (FIG. 11A) likely due to limited sampling by core biopsy. Expression of CCL19 in the melanoma TME has been linked to cancer-associated fibroblasts (CAFs), and CXCL13 to CD8+ exhausted T cells. CCL19 is also strongly expressed in lymph node high endothelial venules. It was noted that strongest induction of CCL19/CXCL13 by anti-PD1 was independent of the number of total CD45+ cells or other immune subpopulations in PDOTS (FIGS. 11B-11D). Therefore, CD45+ and CD45− cell populations from a sample (MGH-16) marked by robust anti-PD1 induced secretion of CCL19 and CXCL13 were sorted, to determine the cellular source of CCL19 and CXCL13 in PDOTS. Indeed, stromal populations including CD90+CD45− cancer-associated fibroblasts, CD31+CD144+ endothelial cells, and tumor cells (CD45−) expressed CCL19 in particular, while CXCL13 was also detected in CD45+ cells (FIG. 11E). Immunohistochemical staining confirmed expression of CCL19 and CXCL13 in stromal elements including cancer-associated fibroblasts (αSMA) and endothelial cells (CD31) (FIG. 11F).

To better understand the relationship between anti-PD1 induced PDOTS cytokine profiles and clinical benefit to ICB, unsupervised hierarchical clustering of cytokine profiles from patients specifically treated with anti-PD-1 therapy was performed. PDOTS from patients with mixed response or progression on anti-PD-1 therapy elaborated multiple immune suppressive cytokines/chemokines (e.g., CCL2) in addition to CCL19/CXCL13 (FIG. 3O). Induction of significantly higher levels of CCL20 and CX3CL1 in patients with no clinical benefit (NCB) to PD-1 blockade (FIG. 12A) was noted, consistent with their lack of association with survival (FIG. 12B) and previous association of CX3CL1 induction with anti-PD-L1 resistance. Several of these immune suppressive cytokines/chemokines induced in PDOTS were also components of an innate PD-1 resistance (IPRES) gene expression signature (FIG. 12B), which correlated with nonresponse but missed statistical significance (p=0.08, FIG. 12C). Serial PDOTS profiling from an individual patient revealed that induction of multiple granulocytic and monocytic chemoattractants predicted infiltration of these respective myeloid populations following disease progression on anti-PD-1 therapy in vivo (FIGS. 12D-12E). These data highlight the potential of this assay to identify cytokines changes associated with ineffective anti-tumor immune responses despite CCL19/CXCL13 induction following ICB.

Higher levels of immune suppressive cytokines were also induced in anti-PD1-resistant B16F10 MDOTS relative to MC38 MDOTS (FIG. 12F), as well as the intermediately resistant CT26 MDOTS model, which elaborated particularly high levels of CCL2 (FIG. 12G). Because of its partial sensitivity to anti-PD1, CT26 model was used to determine whether MDOTS profiling could identify novel combination therapies that overcome resistance. However, neutralization of CCL2 alone failed to enhance PD-1 mediated killing of CT26 MDOTS (FIG. 12H-12I), suggesting the need for alternative strategies that more broadly inhibit immune suppressive signaling within the TME and reactivate T cells.

It was noted that the homologous innate immune signaling kinases TBK1 and IKKε not) only promote autocrine/paracrine cytokine signaling, but also restrain T cell activation, suggesting that a dual impact of TBK1/IKKε inhibition on the TME could enhance anti-tumor activity of PD-1 blockade (FIG. 4A). A novel potent/selective TBK1/IKKε inhibitor Compound 1 (Cmpd1) was synthesized (FIG. 4B, FIGS. 13A-D, Tables S5-1 and S5-2), which lacks JAK inhibitory activity, in contrast to the multitargeted inhibitor momelotinib (CYT387). Cmpd1 effectively blocked immune suppressive cytokine elaboration by CT26 cell line spheroids, without cytotoxic effects (FIG. 4C, FIG. 13E), and enhanced secretion of IL-2 and IFN-γ from purified CD4+ and CD8+ T cells (FIGS. 4D-4E) and IL-2 from Jurkat cells (FIG. 13F). Decreased levels of CCL4, CCL3, and IL-1β with concomitant induction of cytokines involved in activated innate immune responses (e.g., G-CSF) were observed in CT26 MDOTS treated with Cmpd1±anti-PD-1 (FIG. 4F). Ex vivo combination treatment enhanced killing of CT26 MDOTS (FIGS. 4G-4H), which predicted in vivo response with greater tumour control and longer survival than mice treated with Cmpd1 or anti-PD-L1 alone (FIGS. 4I-4K). Reimplantation of CT26 into mice with exceptional responses to combination therapy showed no growth, suggesting immunologic memory for CT26 tumors (FIG. 13F).

Combination treatment in the PD-1 sensitive MC38 MDOTS model enhanced ex vivo killing and in vivo survival, although neither of these reached significance compared to single-agent PD-1/PD-L1 (FIGS. 14A-14D). The intrinsically resistant B16F10 model could not be sensitized with Cmpd1 treatment (FIGS. 14E-14H), possibly due to the relative paucity of immune cells in B16F10 MDOTS compared to CT26 and MC38 MDOTS. Indeed, downregulation of several immune suppressive chemokines (e.g., CCL2, CCL5) in B16F10 MDOTS was observed, but without concomitant induction of G-CSF and related innate immune response cytokines (FIGS. 14A-14B). However, enhanced response to combination treatment with Cmpd1 was confirmed in vivo using a fourth partially anti-PD1 sensitive syngeneic model (MB49 bladder carcinoma), further validating its activity. Importantly, MDOTS responses in three models (CT26, MC38, and B16F10) effectively recapitulated the in vivo response (or lack thereof) to PD-1 blockade+/−TBK1/IKKε inhibition, highlighting the potential of ex vivo screening in MDOTS to develop combination immunotherapies more generally.

Example 3. Transcriptomic Analysis of MDOTS/PDOTS Following Ex Vivo Treatment

RNA is collected from a subset of the MDOTs within the device after the supernatants have been collected and cDNA libraries for RNA sequencing is generated to evaluate global transcriptome changes associated with treatment regimen on single samples per drug treatment. These types of data may be generated from a variety of clinical specimens. The RNA Advance tissue RNA isolation method (Beckman Coulter) is utilized, which is a bead wash based separation technique, which facilitates elution volumes amenable to sample input for RNA-Seq library preparation. Automated library preparation can be performed using as little as 10 ng of good quality RNA. The RNA Access method from Illumina is utilized, which enriches for the coding region of the genome. Libraries are sequenced on the NextSeq500 platform, as 75 bp Single End to generate approximately 20 million reads per sample. With appropriate adaptors, 24 samples are multiplexed on each NextSeq500 run. The concentration [ng/ul], yield [ng] and quality of RNA (high RIN# by bioanalyzer) derived from the MDOTS are more than sufficient to ensure good quality libraries for subsequent sequencing (FIG. 15).

The STAR RNA sequencing alignment tool (Spliced Transcripts Alignment to a Reference) [STAR_2.5.0a]) is utilized to align the data to the genome (RefSeq gene annotations). DeSeq2 is utilized to perform differential expression analysis (±2-fold, P value<0.05). Overlaps between differentially expressed genes and the annotated Immunological gene sets in the Molecular Signature Database or MSigDB (FDR q-value<0.05) are computed. CIBERSORT (Newman A M et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015 May; 12(5):453-7.) is utilized to provide an estimation of the abundances of member cell types in a mixed cell population, including more than 20 immune subsets, using the transcriptomic data generated.

The additional information garnered from whole transcriptome analysis provides a deeper understanding of the biological response to PD-1 immune blockage on its own and in combination with other immune blockade compounds or a MEK inhibitor. This knowledge complements secretion profiling to identify novel mechanisms of both response and resistance. Moreover, computational methods to evaluate the “immunone” including GSEA and CIBERSORT, permit inference of changes in immune cell populations using established gene signatures.

Example 4. RNA-Sequencing of PDOTS/MDOTS for Biomarker Discovery and Novel Target Identification

Bulk RNA-seq was applied to the MDOTS/PDOTS platform as a proof-of-concept to identify candidate biomarkers and potential novel targets for combination therapies in response to inhibition of PD-1.

The patient- and murine-derived organotypic tumor spheroids (PDOTS/MDOTS) platform was utilized to identify novel biomarkers and potential therapeutic targets using RNA-sequencing (RNA-seq). Reproducible induction of cytokines and chemokines (e.g. SOCS3, Pde4b, Pde4d, Adcy5) in response to ex vivo PD-1 blockade using MDOTS and PDOTS was observed (see FIG. 16). Additionally, dual-labeling fluorescence microscopy was used to demonstrate immune-mediated tumor killing. This method for imaging and quantifying immune-mediated tumor killing in combinatorial drug testing represented a novel use of available fluorescent reagents. Evaluation of combinations of different targeted therapies revealed that some therapeutic agents appear to sensitize PDOTS/MDOTS to PD-1 blockade resulting in enhanced immune responses, manifested by alterations in cytokine elaboration, and enhanced tumor killing. In particular, combined TBK1-PD-1 therapy was found to be a novel therapeutic combination to enhance PD-1 response.

Tables with Supportive Data for Example 2:

TABLE S2-1 Tumor Tumor Tumor Tumor Tumor 1.000 2.000 4.000 5.000 6.000 Tumor 1 1.000 0.955 0.890 0.752 0.240 Tumor 2 0.955 1.000 0.835 0.712 0.223 Tumor 4 0.890 0.835 1.000 0.907 0.495 Tumor 5 0.752 0.712 0.907 1.000 0.758 Tumor 6 0.240 0.223 0.495 0.758 1.000 S1 1 0.852 0.900 0.619 0.555 0.197 S1 2 0.975 0.963 0.852 0.699 0.129 S1 3 0.948 0.967 0.756 0.611 0.087 S1 4 0.838 0.821 0.915 0.911 0.676 S1 5 0.558 0.549 0.708 0.802 0.860 S1 6 0.461 0.470 0.554 0.691 0.834 S2 1 0.749 0.788 0.603 0.635 0.455 S2 2 0.948 0.936 0.865 0.816 0.367 S2 3 0.881 0.883 0.696 0.634 0.230 S2 4 0.680 0.651 0.836 0.925 0.825 S2 5 0.308 0.310 0.540 0.713 0.925 S2 6 0.183 0.226 0.383 0.590 0.884 S3 1 0.740 0.776 0.569 0.636 0.459 S3 2 0.827 0.856 0.664 0.688 0.407 S3 3 0.790 0.817 0.548 0.510 0.165 S3 4 0.685 0.675 0.792 0.839 0.768 S3 5 0.300 0.278 0.518 0.567 0.793 S3 6 0.226 0.246 0.430 0.499 0.766

TABLE S2-2 S1 S1 S1 S1 S1 S1 1.000 2.000 3.000 4.000 5.000 6.000 Tumor 1 0.852 0.975 0.948 0.838 0.558 0.461 Tumor 2 0.900 0.963 0.967 0.821 0.549 0.410 Tumor 4 0.619 0.852 0.756 0.915 0.708 0.554 Tumor 5 0.555 0.699 0.611 0.911 0.802 0.691 Tumor 6 0.197 0.129 0.087 0.676 0.860 0.834 S1 1 1.000 0.854 0.932 0.745 0.546 0.553 S1 2 0.854 1.000 0.963 0.776 0.465 0.371 S1 3 0.932 0.963 1.000 0.737 0.447 0.399 S1 4 0.745 0.776 0.737 1.000 0.897 0.803 S1 5 0.546 0.465 0.447 0.897 1.000 0.967 S1 6 0.553 0.371 0.399 0.803 0.967 1.000 S2 1 0.908 0.692 0.778 0.800 0.677 0.672 S2 2 0.862 0.937 0.906 0.863 0.605 0.514 S2 3 0.915 0.849 0.927 0.742 0.493 0.460 S2 4 0.590 0.598 0.547 0.957 0.928 0.835 S2 5 0.290 0.191 0.154 0.749 0.890 0.825 S2 6 0.248 0.081 0.057 0.640 0.822 0.790 S3 1 0.908 0.685 0.776 0.767 0.654 0.666 S3 2 0.937 0.808 0.844 0.808 0.649 0.634 S3 3 0.921 0.764 0.888 0.642 0.428 0.437 S3 4 0.663 0.605 0.580 0.959 0.958 0.889 S3 5 0.283 0.178 0.166 0.720 0.911 0.867 53 6 0.261 0.112 0.101 0.665 0.845 0.794

TABLE S2-3 S2 S2 S2 S2 S2 S2 1.000 2.000 3.000 4.000 5.000 6.000 Tumor 1 0.749 0.948 0.881 0.680 0.308 0.183 Tumor 2 0.788 0.936 0.883 0.651 0.310 0.226 Tumor 4 0.603 0.865 0.696 0.836 0.540 0.383 Tumor 5 0.635 0.816 0.634 0.925 0.713 0.590 Tumor 6 0.455 0.367 0.230 0.825 0.925 0.884 S1 1 0.908 0.862 0.915 0.590 0.290 0.248 S1 2 0.692 0.937 0.849 0.598 0.191 0.081 S1 3 0.778 0.906 0.927 0.547 0.154 0.057 S1 4 0.800 0.863 0.742 0.957 0.749 0.640 S1 5 0.677 0.605 0.493 0.928 0.890 0.822 S1 6 0.672 0.514 0.460 0.835 0.825 0.790 S2 1 1.000 0.833 0.898 0.735 0.567 0.527 S2 2 0.833 1.000 0.901 0.751 0.425 0.323 S2 3 0.898 0.901 1.000 0.616 0.290 0.184 S2 4 0.735 0.751 0.616 1.000 0.872 0.767 S2 5 0.567 0.425 0.290 0.872 1.000 0.970 S2 6 0.527 0.323 0.184 0.767 0.970 1.000 S3 1 0.984 0.835 0.901 0.707 0.529 0.493 S3 2 0.945 0.920 0.890 0.717 0.481 0.443 S3 3 0.893 0.816 0.976 0.517 0.217 0.139 S3 4 0.779 0.741 0.625 0.970 0.862 0.782 S3 5 0.485 0.327 0.243 0.792 0.894 0.836 S3 6 0.510 0.298 0.201 0.747 0.929 0.920

TABLE S2-4 S3 S3 S3 S3 S3 S3 1.000 2.000 3.000 4.000 5.000 6.000 Tumor 1 0.740 0.827 0.790 0.685 0.300 0.226 Tumor 2 0.776 0.856 0.817 0.675 0.278 0.246 Tumor 4 0.569 0.664 0.548 0.792 0.518 0.430 Tumor 5 0.636 0.688 0.510 0.839 0.567 0.499 Tumor 6 0.459 0.407 0.165 0.768 0.793 0.766 S1 1 0.908 0.937 0.921 0.663 0.283 0.261 S1 2 0.685 0.808 0.764 0.605 0.178 0.112 S1 3 0.776 0.844 0.888 0.580 0.166 0.101 S1 4 0.767 0.808 0.642 0.959 0.720 0.665 S1 5 0.654 0.649 0.428 0.958 0.911 0.845 S1 6 0.666 0.634 0.437 0.889 0.867 0.794 S2 1 0.984 0.945 0.893 0.779 0.485 0.510 S2 2 0.835 0.920 0.816 0.741 0.327 0.298 S2 3 0.901 0.890 0.976 0.625 0.243 0.201 S2 4 0.707 0.717 0.517 0.970 0.792 0.747 S2 5 0.529 0.481 0.217 0.862 0.894 0.929 S2 6 0.493 0.443 0.139 0.782 0.836 0.920 S3 1 1.000 0.960 0.913 0.746 0.426 0.440 S3 2 0.960 1.000 0.874 0.763 0.387 0.394 S3 3 0.913 0.874 1.000 0.550 0.181 0.146 S3 4 0.746 0.763 0.550 1.000 0.849 0.812 S3 5 0.426 0.387 0.181 0.849 1.000 0.955 S3 6 0.440 0.394 0.146 0.812 0.955 1.000

TABLE S3 Transcripts Per Million Normalized Counts CCL19 CXCL13 ID Response CCL19 CXCL13 Pt ID Response (ENSG00000172724) (ENSG00000156234) Pt13 R 34.698109 2519.38443 Pt13 R 1.168351014 1.450293862 Pt15 R 368.803957 958.479364 Pt15 R 7.162930953 0.318252625 Pt19 R 1958.97151 620.707828 Pt19 R 13.49446269 0.073098545 Pt2 R 290.527532 1198.6162 Pt2 R 7.401911739 0.522072463 Pt27A R 209.760872 1416.41918 Pt27A R 7.057272238 0.814700951 Pt27B R 127.405123 460.732479 Pt27B R 4.111967591 0.254217624 Pt28 R 1952.44983 2324.597 Pt28 R 40.56616838 0.825706707 Pt35 R 95.3399393 539.624057 Pt35 R 3.445558222 0.333403426 Pt37 R 97.0628571 349.174174 Pt37 R 2.033195626 0.125043823 Pt38 R 9077.47447 44808.3318 Pt38 R 292.4756557 24.68183797 Pt4 R 158.462804 383.601214 Pt4 R 2.601765411 0.107674982 Pt5 R 0.8957807 94.056973 Pt5 R 0.038933398 0.069888488 Pt6 R 1.44330175 90.2063594 Pt6 R 0.020724471 0.022144073 Pt8 R 617.842921 243.736198 Pt8 R 12.63014518 0.085181314 Pt9 R 1131.85131 641.694215 Pt9 R 35.53789234 0.344448618 Pt1 NR 2340.48615 479.579124 Pt1 NR 99.54999655 0.348730135 Pt10 NR 2.70089632 2584.08255 Pt10 NR 0.098714409 1.614630139 Pt12 NR 292.02708 93.1555918 Pt12 NR 8.617132617 0.046994022 Pt16 NR 14.8144533 421.153742 Pt14 NR 9.131829845 0.112841472 Pt14 NR 221.968265 160.438202 Pt16 NR 0.360470362 0.17519376 Pt20 NR 3001.54512 6437.79678 Pt20 NR 49.36256271 1.810023107 Pt22 NR 1426.52919 960.941811 Pt22 NR 21.09294252 0.242911252 Pt23 NR 15.1942229 2322.92855 Pt23 NR 0.229044285 0.598647058 Pt25 NR 944.629262 879.267764 Pt25 NR 11.4526496 0.182246738 Pt29 NR 420.240506 1498.70041 Pt29 NR 11.97953537 0.73038345 Pt31 NR 39.9689397 296.01996 Pt31 NR 0.909356479 0.115140091 Pt32 NR 4.86573555 259.830278 Pt32 NR 0.18150561 0.165701082 Pt7 NR 217.069727 429.20605 Pt7 NR 4.459248487 0.150737839 15 responders 13 non-resonders

TABLE S4A Melanoma Patient Samples-Patient Treatment Details Samples Treatment Clinical Benefit/Response 148-S9 pre-PD-1-combo (on trial) NCB (mixed response → 148-S10 post-PD-1-combo (on trial) (209 days) progressive disease) 208-S11 pre-CTLA-4; pre-PD-1 NCB (progression) 208-S12 on-CTLA-4 (42 days); pre-PD-1 208-S13 post-CTLA-4 (182 days); pre-PD-1 208-S14 post-CTLA-4 (245 days); on-PD-1 (63 days) 27-S1 post-BRAFi (479 days); pre-PD-1 NCB (progression) 27-S2 post-BRAFi (960 days); on-PD-1 (31 days) 39-S15 post-BRAFi (393 days); post-IL2 (388 days); post-CTLA-4 NCB (mixed response → (153 days); pre-BRAFi/MEKi; pre-PD-1 progressive disease 39-S16 post-BRAFi (540 days); post-IL2 (535 days); post-CTLA-4 (300 days); post-BRAFi/MEKi (54 days); on-PD-1 (21 days) 39-S17 post-BRAFi (607 days); post-IL2 (602 days); post-CTLA-4 (367 days); post-BRAFi/MEKi (121 days); on-PD-1 (88 days) 42-S3 post-CTLA-4 (176 days); post-BRAFi/MEKi (64 days); NCB (progression) pre-PD-1 42-S4 post-CTLA-4 (214 days); post-BRAFi/MEKi (102 days); on-PD-1 (38 days) 42-S5 post-CTLA-4 (250 days); post-BRAFi/MEKi (138 days); post-PD-1 (74 days) 62-S6 pre-CTLA-4; pre-PD-1 NCB (stable disease → disease 62-S7 post-CTLA-4 (235 days); on-PD-1 (3 days) progression) 62-S8 post-CTLA-4 (277 days); on-PD-1 (45 days) 272-S1 pre-CTLA-4 CB (near complete response, 272-S2 post-CTLA-4 (47 days); pre-PD-1 PD-1 stopped due to irAE, 272-S3 post-CTLA-4 (437 days); post-PD-1 (346 days) eventual progression off therapy) 422-S1 pre-PD-1, pre-CTLA-4 CB (excellent response after ipi- 422-S2 on-PD-1, on-CTLA-4 nivo → nivo) 51-S1 pre-PD-L1 CB (stable disease with a single 51-S2 Post-PD-L1 (224 days) escape lesion) 98-S1 post-PD-1 (83 days); pre-CTLA-4 CB (mixed response → 98-S2 Post-PD-1 (109 days); post-CTLA-4 (25 days) response) 98-S3 post-PD-1 (182 days); post-CTLA-4 (98 days)

TABLE S4B-1 Samples 148-S9 148-S10 208-S11 208-S12 208-S13 208-S14 27-S1 27-S2 Treatment post- post- post-PD- post- CTLA-4 post- BRAFi 1-combo on- CTLA-4 (245 BRAFi (960 pre-PD- (on trial) pre- CTLA-4 (182 days); on- (479 days); on- 1-combo (209 CTLA-4; (42 days); days); PD-1 (63 days); PD-1 (31 (on trial) days) pre-PD-1 pre-PD-1 pre-PD-1 days) pre-PD-1 days) CCL19 0.15687084 0.41913344 1.98815132 4.59582353 3.45513526 8.77085298 0.1 0.93715502 CXCL13 0.26803097 2.38711763 0.09436038 24.7654719 2.17496489 11.6557472 1.27418346 0.6404927 CCL2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 CCL7 0.1 0.352523 0.13934883 0.1 0.1 0.32786454 0.1 0.1 CCL8 19.5526419 29.918033 0.90971542 3.97934158 5.89116018 8.66865469 0.36852681 3.80785605 CCL13 24.0118925 82.8961538 3.06991672 9.11382191 6.00656079 10.3634372 0.36047157 0.30199656 IL10 2.70808608 3.17659032 0.41855817 1.41409955 0.68911285 1.88752859 0.09419912 0.23675495 VEGFA 3.53392266 4.83525269 1.29428459 0.86705549 1.65186515 1.23934008 1.5851421 2.89436628 VEGFC 6.12754266 8.3234783 0.81574911 2.3208504 1.85041997 1.47147983 1.248408 2.33787985 CCR7 0.43889039 0.90613397 0.42139498 3.5517162 0.97129671 4.51119789 0.11380507 0.42904724 CXCR5 0.06942884 0.13912696 0.18331834 0.39116295 0.20120982 0.60384444 0.1 0.04147717 AXL 32.5031535 60.0635857 2.91859483 8.55069013 6.30519042 4.63247743 2.56483473 3.61622621 GZMA 2.51550488 9.76148303 3.16280085 53.720088 30.132477 28.5755234 1.53750529 13.8827918 GZMB 3.13000293 3.09735564 0.7346123 33.0483114 4.43469902 8.64210075 3.47191043 10.5267372 IFNGR1 51.4518655 56.8050947 54.1265708 61.4638002 58.8209997 82.2106075 43.6363806 28.2519413 TNF 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 IL2 0.13457249 0.17977794 0.1 0.1 0.1 0.16720274 0.1 0.1 IFNG 0.26670627 0.23753197 0.1 3.00525274 0.72140516 2.09871115 0.38036581 1.06221195 0.1 Below quantification

TABLE S4B-2 Samples 39-S15 39-S16 39-S17 42-S3 42-S4 42-S5 62-S6 62-S7 Treatment post- post- BRAFi BRAFi (540 (607 days); days); post-IL2 post-IL2 post- (535 (602 BRAFi days); days); (393 days); post- post- post- post- post-IL2 CTLA-4 CTLA-4 post- CTLA-4 CTLA-4 (388 days); (300 (367 CTLA-4 (214 (250 post- days); days); (176 days); days); CTLA-4 post- post- days); post- post- post- (153 days); BRAFi/ BRAFi/ post- BRAFi/ BRAFi/ CTLA-4 pre- MEKi (54 MEKi (121 BRAFi/ MEKi (102 MEKi (138 pre- (235 BRAFi/ days); on- days); on- MEKi (64 days); on- days); CTLA- days); MEKi; pre- PD-1 (21 PD-1 (88 days); PD-1 (38 post-PD-1 4; pre- on-PD-1 PD-1 days) days) pre-PD-1 days) (74 days) PD-1 (3 days) CCL19 0.1 7.17238179 0.57691197 1.23267021 5.18691585 6.33513418 0.1 0.19283266 CXCL13 1.62907579 2.78518137 13.80004 0.23401686 21.2470659 3.96889863 0.1 0.98842702 CCL2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 CCL7 0.2830323 0.41130796 0.48522669 0.1 0.83895949 1.24327654 0.1 0.1 CCL8 3.97261692 2.50614458 2.32299537 2.93296153 34.1765182 59.2506107 7.98116673 4.1293583 CCL13 2.57546133 5.90954174 1.08446841 3.6412366 67.6625745 58.3524709 5.93524222 8.85494803 IL10 1.9128064 1.50997511 6.1537277 0.34601269 5.87990461 2.48959659 0.16767663 0.64954159 VEGFA 2.44542296 1.59918098 1.08303658 0.29859241 2.57328173 0.92074409 0.72348459 1.68157005 VEGFC 0.99412394 1.76571995 1.00996294 0.60692541 3.9945039 0.90110433 1.56860848 1.77229407 CCR7 0.21397451 0.8706652 0.88040393 0.52253673 0.9133338 0.53710072 0.20257569 0.09809159 CXCR5 0.0372339 0.14429073 0.17022212 0.0909271 0.44147241 0.0934614 0.1 0.1 AXL 3.15217802 5.9937903 5.59225163 2.69996776 10.0967011 3.89711811 4.64898024 4.8257931 GZMA 5.26766769 14.8122602 18.7958475 3.45129418 118.364242 42.5698517 8.66651831 5.88984997 GZMB 3.6058497 22.4059016 21.3166185 3.64372548 109.390225 31.8348999 1.03001359 2.13752208 IFNGR1 81.0920132 110.98998 60.1500121 79.9433286 95.0516258 75.0677163 0.1 35.6153856 TNF 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 IL2 0.14433941 0.1 0.82484505 0.1 0.1 0.36230859 0.1 0.1 IFNG 0.66748061 0.46190268 3.16050183 0.11643014 7.80107938 4.30830872 0.56421667 0.32784729 0.1 Below quantification

TABLE S4B-3 Samples 62-S8 272-S1 272-S2 272-S3 422-S1 422-S2 Treatment post- post- CTLA-4 CTLA (277 post- -4 (437 days); CTLA- days); pre- on- on- 4 (47 post- PD-1, PD-1, PD-1 pre- days); PD-1 pre- on- (45 CTLA- pre- (346 CTLA- CTLA- days) 4 PD-1 days) 4 4 CCL19 0.18082453 30.8026747 81.8439915 30.3310126 49.1698251 569.522382 CXCL13 0.20597232 143.121621 197.444029 42.1785257 88.565516 236.913118 CCL2 0.1 0.1 0.1 0.1 0.1 0.1 CCL7 0.1 2.26838847 2.20958272 4.55339377 27.1500865 0.1 CCL8 0.09928753 38.0092355 21.2212318 12.1190886 142.838439 3.00565688 CCL13 1.16540776 7.7380948 10.0937847 4.97652335 13.0430495 2.22349876 IL10 0.22840994 10.9175298 12.1675798 3.6530185 2.56684581 2.03367129 VEGFA 1.21549229 1.59027526 1.89991979 4.36289443 1.41618926 0.51813138 VEGFC 0.94967388 1.66183682 2.86889762 1.731475 1.96825775 2.46115994 CCR7 0.3219412 8.27974664 12.7854505 4.44863917 5.84631976 95.5634831 CXCR5 0.52019769 1.09942208 2.21362828 0.79868685 0.37596741 48.1180912 AXL 2.4522467 56.6522478 74.8405834 13.3027932 10.9127259 19.1432302 GZMA 3.58999916 80.8064715 125.257307 46.3160997 41.8012 37.8345867 GZMB 7.61677215 17.1664256 16.4009527 3.82328583 10.1578792 4.1352438 IFNGR1 11.8733792 57.0563904 61.1826911 37.3127656 44.6747933 85.6737313 TNF 0.1 1.26258841 1.58476345 0.69407351 1.36758178 2.61714127 IL2 0.1 0.1 0.1 0.1 0.1 0.1 IFNG 0.20495433 10.2969456 11.6529517 2.83209437 2.88850742 1.74662482 Samples 51-S1 51-S2 98-S1 98-S2 98-S3 Treatment post- post- post- PD-1 PD-1 PD-1 (109 (182 (83 days); days); post- days); post- post- PD-L1 pre- CTLA- CTLA- pre- (224 CTLA- 4 (25 4 (98 PD-Ll days) 4 days) days) CCL19 31.365808 32.4152798 0.17967977 0.53928875 47.9201706 CXCL13 16.4200002 79.6634246 1.33034424 1.36021174 68.8004261 CCL2 0.1 0.1 0.1 0.1 0.1 CCL7 0.85296606 0.06224591 0.1511243 0.25919012 0.48076933 CCL8 6.96055707 12.0283136 1.28256651 2.15740095 18.2040065 CCL13 24.9771521 3.04071984 0.79614548 0.49652815 23.4856381 IL10 2.3790281 1.43340819 0.26479124 0.55145316 2.32656264 VEGFA 0.97385307 0.71259811 2.69306142 6.84424133 0.76154607 VEGFC 6.2059211 0.70448349 0.8551934 1.01153397 5.75394032 CCR7 5.96945609 8.15050896 0.13710131 0.05878489 4.26465798 CXCR5 0.30457195 1.75237544 0.01988094 0.01704869 0.92762141 AXL 2.54442739 29.894754 0.48020963 0.52945552 144.038705 GZMA 10.1174052 40.9634229 1.79255175 1.87878039 27.1754305 GZMB 8.29444931 14.8478181 2.44928242 3.15592022 18.753749 IFNGR1 184.213974 47.254564 22.8699314 32.4953981 124.279512 TNF 0.33169142 0.45183519 0.11821037 0.04054803 0.73206497 IL2 0.1 0.1 0.1 0.1 0.1 IFNG 0.12315714 4.90717196 0.0509142 0.04366094 10.0962879 0.1 Below quantification

TABLE S4B-4 FC 148 208a 208b 208c 27 39a 39b 42a 42b CCL19 2.67 2.31 1.74 4.41 9.37 71.72 5.77 4.21 5.14 CXCL13 8.91 262.46 23.05 123.52 0.50 1.71 8.47 90.79 16.96 CCL2 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 CCL7 3.53 0.72 0.72 2.35 1.00 1.45 1.71 8.39 12.43 CCL8 1.53 4.37 6.48 9.53 10.33 0.63 0.58 11.65 20.20 CCL13 3.45 2.97 1.96 3.38 0.84 2.29 0.42 18.58 16.03 IL10 1.17 3.38 1.65 4.51 2.51 0.79 3.22 16.99 7.20 VEGFA 1.37 0.67 1.28 0.96 1.83 0.65 0.44 8.62 3.08 VEGFC 1.36 2.85 2.27 1.80 1.87 1.78 1.02 6.58 1.48 CCR7 2.06 8.43 2.30 10.71 3.77 4.07 4.11 1.75 1.03 CXCR5 2.00 2.13 1.10 3.29 0.41 3.88 4.57 4.86 1.03 AXL 1.85 2.93 2.16 1.59 1.41 1.90 1.77 3.74 1.44 GZMA 3.88 16.98 9.53 9.03 9.03 2.81 3.57 34.30 12.33 GZMB 0.99 44.99 6.04 11.76 3.03 6.21 5.91 30.02 8.74 IFNGR1 1.10 1.14 1.09 1.52 0.65 1.37 0.74 1.19 0.94 TNF 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 IL2 1.34 1.00 1.00 1.67 1.00 0.69 5.71 1.00 3.62 IFNG 0.89 30.05 7.21 20.99 2.79 0.69 4.73 67.00 37.00

TABLE S4B-5 FC 62a 62b 272a 272b 422 51 98a 98b CCL19 1.93 1.81 2.66 0.98 11.58 1.03 3.00 266.70 CXCL13 9.88 2.06 1.38 0.29 2.68 4.85 1.02 51.72 CCL2 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 CCL7 1.00 1.00 0.97 2.01 0.00 0.07 1.72 3.18 CCL8 0.52 0.01 0.56 0.32 0.02 1.73 1.68 14.19 CCL13 1.49 0.20 1.30 0.64 0.17 0.12 0.62 29.50 IL10 3.87 1.36 1.11 0.33 0.79 0.60 2.08 8.79 VEGFA 2.32 1.68 1.19 2.74 0.37 0.73 2.54 0.28 VEGFC 1.13 0.61 1.73 1.04 1.25 0.11 1.18 6.73 CCR7 0.48 1.59 1.54 0.54 16.35 1.37 0.43 31.11 CXCR5 1.00 5.20 2.01 0.73 127.98 5.75 0.86 46.66 AXL 1.04 0.53 1.32 0.23 1.75 11.75 1.10 299.95 GZMA 0.68 0.41 1.55 0.57 0.91 4.05 1.05 15.16 GZMB 2.08 7.39 0.96 0.22 0.41 1.79 1.29 7.66 IFNGR1 356.15 118.73 1.07 0.65 1.92 0.26 1.42 5.43 TNF 1.00 1.00 1.26 0.55 1.91 1.36 0.34 6.19 IL2 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 IFNG 0.58 0.36 1.13 0.28 0.60 39.84 0.86 198.30

TABLE S4B-6 L2FC 148 208a 208b 208c 27 39a 39b 42a 42b CCL19 1.42 1.21 0.80 2.14 3.23 6.16 2.53 2.07 2.36 CXCL13 3.15 8.04 4.53 6.95 −0.99 0.77 3.08 6.50 4.08 CCL2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 CCL7 1.82 −0.48 −0.48 1.23 0.00 0.54 0.78 3.07 3.64 CCL8 0.61 2.13 2.70 3.25 3.37 −0.66 −0.77 3.54 4.34 CCL13 1.79 1.57 0.97 1.76 −0.26 1.20 −1.25 4.22 4.00 IL10 0.23 1.76 0.72 2.17 1.33 −0.34 1.69 4.09 2.85 VEGFA 0.45 −0.58 0.35 −0.06 0.87 −0.61 −1.18 3.11 1.62 VEGFC 0.44 1.51 1.18 0.85 0.91 0.83 0.02 2.72 0.57 CCR7 1.05 3.08 1.20 3.42 1.91 2.02 2.04 0.81 0.04 CXCR5 1.00 1.09 0.13 1.72 −1.27 1.95 2.19 2.28 0.04 AXL 0.89 1.55 1.11 0.67 0.50 0.93 0.83 1.90 0.53 GZMA 1.96 4.09 3.25 3.18 3.17 1.49 1.84 5.10 3.62 GZMB −0.02 5.49 2.59 3.56 1.60 2.64 2.56 4.91 3.13 IFNGR1 0.14 0.18 0.12 0.60 −0.63 0.45 −0.43 0.25 −0.09 TNF 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 IL2 0.42 0.00 0.00 0.74 0.00 −0.53 2.51 0.00 1.86 IFNG −0.17 4.91 2.85 4.39 1.48 −0.53 2.24 6.07 5.21

TABLE S4B-7 L2FC 62a 62b 272a 272b 422 51 98a 98b CCL19 0.95 0.85 1.41 −0.02 3.53 0.05 1.59 8.06 CXCL13 3.31 1.04 0.46 −1.76 1.42 2.28 0.03 5.69 CCL2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 CCU/ 0.00 0.00 −0.04 1.01 −8.08 −3.78 0.78 1.67 CCL8 −0.95 −6.33 −0.84 −1.65 −5.57 0.79 0.75 3.83 CCL13 0.58 −2.35 0.38 −0.64 −2.55 −3.04 −0.68 4.88 IL10 1.95 0.45 0.16 −1.58 −0.34 −0.73 1.06 3.14 VEGFA 1.22 0.75 0.26 1.46 −1.45 −0.45 1.35 −1.82 VEGFC 0.18 −0.72 0.79 0.06 0.32 −3.14 0.24 2.75 CCR7 −1.05 0.67 0.63 −0.90 4.03 0.45 −1.22 4.96 CXCR5 0.00 2.38 1.01 −0.46 7.00 2.52 −0.22 5.54 AXL 0.05 −0.92 0.40 −2.09 0.81 3.55 0.14 8.23 GZMA −0.56 −1.27 0.63 −0.80 −0.14 2.02 0.07 3.92 GZMB 1.05 2.89 −0.07 −2.17 −1.30 0.84 0.37 2.94 IFNGR1 8.48 6.89 0.10 −0.61 0.94 −1.96 0.51 2.44 TNF 0.00 0.00 0.33 −0.86 0.94 0.45 −1.54 2.63 IL2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 IFNG −0.78 −1.46 0.18 −1.86 −0.73 5.32 −0.22 7.63

TABLE S5-1 Project SSBK10488_30712; provides data for Cmpd1 (1000 μM). % % % Dev In- In- In- Dup Donor Acceptor Reaction hibition hibition hibition Differ- Inter- Inter- Kinase Part#/ Inter- ATP Kinase mutant Technology 1 2 Avg ence ference ference Z′ Lot# ference Km TBK1 ZLYTE 91 99 95 8 Pass Pass 0.83 PV3504/857011 Pass app CDC7/DBF4 LanthaScreen 100 97 98 3 Pass Pass 0.84 PV6274/1576890 Binding MAPK15 (ERK7) LanthaScreen 100 100 100 0 Pass Pass 0.93 PV6181/1570972 Binding Km IKBKE (IKK ZLYTE 106 103 105 3 Pass Pass 0.8 PV4875/853377 Pass app epsilon) Km CSF1R (FMS) ZLYTE 91 96 93 6 Pass Pass 0.79 PV3249/662393 Pass app STK17A (DRAK1) LanthaScreen 101 101 101 0 Pass Pass 0.9 PV3783/902537 Binding TGFBR2 LanthaScreen 92 95 93 3 Pass Pass 0.79 PV6122/862447 Binding PLK4 LanthaScreen 96 95 96 1 Pass Pass 0.96 PV6394/1577044 Binding Km LRRK2 Adapta 99 100 100 1 Pass Pass 0.76 PV4873/1106714 app Km STK22D (TSSK1) ZLYTE 99 95 97 3 Pass Pass 0.88 PV3505/1211826 Pass app Km PRKD2 (PKD2) ZLYTE 99 97 98 2 Pass Pass 0.8 PV3758/34015 Pass app Km MKNK1 (MNK1) ZLYTE 99 100 100 1 Pass Pass 0.77 PV6023/1405297 Pass app Km PRKD1 (PKC mu) ZLYTE 100 95 98 5 Pass Pass 0.86 PV3791/34226 Pass app Km MARK4 ZLYTE 96 93 95 3 Pass Pass 0.8 PV3851/304213 Pass app Km MARK3 ZLYTE 98 94 96 4 Pass Pass 0.73 PV4819/830446 Pass app Km PAK4 ZLYTE 91 90 90 1 Pass Pass 0.73 PV4212/35324 Pass app MLCK (MLCK2) LanthaScreen 92 93 93 0 Pass Pass 0.56 PV3835/34028 Binding ULK3 LanthaScreen 101 104 102 3 Pass Pass 0.82 PV6436/1579414 Binding Km IRAK1 Adapta 94 96 95 1 Pass Pass 0.91 PV4403/880118 app Km BRSK1 (SAD1) ZLYTE 92 89 90 4 Pass Pass 0.91 PV4333/36097 Pass app SIK3 LanthaScreen 98 95 96 2 Pass Pass 0.73 PV6403/1577057 Binding Km PRKCN (PKD3) ZLYTE 98 96 97 2 Pass Pass 0.74 PV3692/1252690 Pass app STK16 (PKL12) LanthaScreen 95 93 94 2 Pass Pass 0.76 PV4311/36847 Binding ULK2 LanthaScreen 86 90 88 4 Pass Pass 0.9 PV6433/1579413 Binding Km LRRK2 G2019S y Adapta 99 100 100 1 Pass Pass 0.88 PV4881/933637 app Km LRRK2 G2019S FL y Adapta 100 99 99 1 Pass Pass 0.81 A15200PT/50078 app Km LRRK2 12020T y Adapta 100 98 99 2 Pass Pass 0.84 PV5854/902533 app Km LRRK2 FL Adapta 98 98 98 0 Pass Pass 0.88 A15197PT/11476 app 93 Km LRRK2 R1441C y Adapta 99 95 97 4 Pass Pass 0.8 PV5858/902531 app KIT D816H y LanthaScreen 90 94 92 4 Pass Pass 0.82 PV6196/1570980 Binding ULK1 LanthaScreen 91 92 92 1 Pass Pass 0.8 PV6430/1579415 Binding ACVR1 (ALK2) y LanthaScreen 88 93 91 5 Pass Pass 0.88 PV6232/1578464 R206H Binding KIT A829P y LanthaScreen 91 90 90 0 Pass Pass 0.89 PV6193/1570981 Binding Km AURKA (Aurora ZLYTE 91 86 89 5 Pass Pass 0.84 PV3612/32155 Pass app A) EIF2AK2 (PKR) LanthaScreen 90 89 89 1 Pass Pass 0.8 PV4821/374655 Binding STK17B (DRAK2) LanthaScreen 94 84 89 10 Pass Pass 0.6 PV6328/1575526 Binding CLK4 LanthaScreen 87 89 88 2 Pass Pass 0.81 PV3839/827665 Binding Km SNF1LK2 ZLYTE 88 88 88 0 Pass Pass 0.66 PV4792/719848 Pass app MKNK2 (MNK2) LanthaScreen 86 88 87 2 Pass Pass 0.86 PV5607/811381 Binding Km MAP4K4 (HGK) ZLYTE 86 86 86 0 Pass Pass 0.74 PV3687/792773 Pass app Km MARK1 (MARK) ZLYTE 85 87 86 3 Pass Pass 0.89 PV4395/1081574 Pass app Km FYN ZLYTE 85 85 85 0 Pass Pass 0.7 P3042/1191778 Pass app RIPK2 LanthaScreen 84 86 85 1 Pass Pass 0.93 PV4213/35334 Binding ACVR1 (ALK2) LanthaScreen 85 84 84 1 Pass Pass 0.92 PV4877/676188 Binding Km MARK2 ZLYTE 86 82 84 4 Pass Pass 0.88 PV3878/877056 Pass app KIT D816V y LanthaScreen 83 83 83 1 Pass Pass 0.74 PV6199/1570986 Binding Km NUAK1 (ARK5) Adapta 83 83 83 0 Pass Pass 0.83 PV4127/1401900 app Km PDGFRA V561D y ZLYTE 85 81 83 4 Pass Pass 0.84 PV4680/1113217 Pass app TLK2 LanthaScreen 84 81 83 3 Pass Pass 0.91 PV6424/1578677 Binding Km FLT3 D835Y y ZLYTE 83 81 82 2 Pass Pass 0.81 PV3967/308809 Pass app Km PHKG2 ZLYTE 83 79 81 4 Pass Pass 0.85 PV4555/37321 Pass app Km PDK1 Direct ZLYTE 85 74 79 11 Pass Pass 0.71 P3001/1394674 Pass app Km CHEK1 (CHK1) ZLYTE 78 78 78 1 Pass Pass 0.74 P3040/28702 Pass app DMPK LanthaScreen 76 79 78 2 Pass Pass 0.84 PV3784/802854 Binding Km PAK7 (KIAA1264) ZLYTE 77 79 78 2 Pass Pass 0.84 PV4405/36846 Pass app Km PLK3 ZLYTE 80 76 78 5 Pass Pass 0.8 PV3812/38812 Pass app Km PDGFRA D842V y ZLYTE 77 73 75 4 Pass Pass 0.89 PV4203/26969 Pass app Km JAK3 ZLYTE 73 73 73 1 Pass Pass 0.86 PV3855/1017963 Pass app CDK16 LanthaScreen 70 73 71 3 Pass Pass 0.81 PV6379/1577049 (PCTK1)/cyclin Y Binding Km MAP3K9 (MLK1) ZLYTE 68 73 70 5 Pass Pass 0.84 PV3787/1095726 Pass app Km NEK1 ZLYTE 68 70 69 3 Pass Pass 0.82 PV4202/880120 Pass app Km RET V804L y ZLYTE 71 66 69 5 Pass Pass 0.85 PV4397/36640 Pass app Km MINK1 ZLYTE 66 70 68 4 Pass Pass 0.76 PV3810/1081579 Pass app ABL1 M351T y LanthaScreen 65 69 67 4 Pass Pass 0.67 PV6151/1570962 Binding Km JAK2 ZLYTE 67 68 67 1 Pass Pass 0.8 PV4210/784633 Pass app KIT N822K y LanthaScreen 66 67 66 1 Pass Pass 0.71 PV6310/1576886 Binding Km TYK2 ZLYTE 65 64 64 1 Pass Pass 0.88 PV4790/884908 Pass app FLT3 ITD LanthaScreen 64 62 63 2 Pass Pass 0.72 PV6190/1570961 Binding Km MYLK2 ZLYTE 65 60 63 5 Pass Pass 0.67 PV3757/36606 Pass app (skMLCK) 100 BRAF V599E y ZLYTE 63 61 62 2 Pass Pass 0.92 PV3849/910409 Pass Km FLT4 (VEGFR3) ZLYTE 64 60 62 5 Pass Pass 0.87 PV4129/38454 Pass app Km PLK2 ZLYTE 60 64 62 4 Pass Pass 0.9 PV4204/38798 Pass app Km ABL1 G250E y ZLYTE 60 61 60 1 Pass Pass 0.9 PV3865/34529 Pass app ABL1 H396P y LanthaScreen 58 60 59 2 Pass Pass 0.74 PV6148/1570966 Binding MAP3K10 (MLK2) LanthaScreen 58 60 59 2 Pass Pass 0.96 PV3877/1138344 Binding BMPR1B (ALK6) LanthaScreen 56 60 58 3 Pass Pass 0.81 PV6235/1578462 Binding Km CHUK (IKK alpha) Adapta 65 50 58 15 Pass Pass 0.79 PV4310/1110228 app DDR2 T654M y LanthaScreen 56 57 57 1 Pass Pass 0.79 PV6175/1570973 Binding MAP4K1 (HPK1) LanthaScreen 59 55 57 3 Pass Pass 0.72 PV6355/1575528 Binding MAPK8 (JNK1) LanthaScreen 57 56 57 1 Pass Pass 0.83 PV3319/1354818 Binding Km SRC N1 ZLYTE 54 60 57 6 Pass Pass 0.91 P2904/21068 Pass app STK33 LanthaScreen 59 55 57 4 Pass Pass 0.91 PV4343/798867 Binding TGFBR1 (ALK5) LanthaScreen 56 58 57 2 Pass Pass 0.91 PV5837/562479 Binding DAPK2 LanthaScreen 60 53 56 7 Pass Pass 0.64 PV3614/32159 Binding SIK1 LanthaScreen 57 54 56 2 Pass Pass 0.93 PV6445/1601253 Binding Km AMPK A1/B1/G1 ZLYTE 58 53 55 5 Pass Pass 0.9 PV4672/1046028 Pass app Km ABLI Y253F y ZLYTE 61 48 54 12 Pass Pass 0.92 PV3863/34531 Pass app CDK14 LanthaScreen 56 51 54 5 Pass Pass 0.56 PV6382/1577046 (PFTK1)/cyclin Y Binding DYRK2 LanthaScreen 54 53 54 1 Pass Pass 0.57 PV6331/1578676 Binding Km FGR ZLYTE 53 53 53 0 Pass Pass 0.94 P3041/26670 Pass app KIT Y823D y LanthaScreen 47 59 53 12 Pass Pass 0.67 PV6322/1579412 Binding Km LYN B ZLYTE 56 50 53 6 Pass Pass 0.8 P2907/21076 Pass app NUAK2 LanthaScreen 54 52 53 1 Pass Pass 0.65 PV6376/1607389 Binding TEK (TIE2) y LanthaScreen 53 52 53 0 Pass Pass 0.6 PV6229/1570987 Y1108F Binding Km YES1 ZLYTE 55 51 53 4 Pass Pass 0.84 A15557/50645 Pass app BRAF V599E y LanthaScreen 50 53 52 3 Pass Pass 0.89 PV3849/910409 Binding Km JAK2 JH1 JH2 ZLYTE 54 50 52 4 Pass Pass 0.84 PV4336/463344 Pass app V617F Km KDR (VEGFR2) ZLYTE 51 53 52 2 Pass Pass 0.85 PV3660/1223246 Pass app Km ABL1 E255K y ZLYTE 53 50 51 3 Pass Pass 0.79 PV3864/34528 Pass app Km AURKB (Aurora ZLYTE 54 48 51 6 Pass Pass 0.78 PV6130/857013 Pass app B) BMPR1A (ALK3) LanthaScreen 51 51 51 0 Pass Pass 0.82 PV6038/670004 Binding Km DAPK3 (ZIPK) ZLYTE 52 49 51 3 Pass Pass 0.68 PV3686/1083962 Pass app PKN2 (PRK2) LanthaScreen 51 52 51 2 Pass Pass 0.93 PV3879/555959 Binding Km RET Y791F y ZLYTE 57 43 50 14 Pass Pass 0.91 PV4396/36639 Pass app STK38 (NDR) LanthaScreen 51 49 50 2 Pass Pass 0.81 PV6370/1575531 Binding Km ABL1 ZLYTE 48 51 49 4 Pass Pass 0.88 P3049/1012910 Pass app BMPR2 LanthaScreen 50 47 49 3 Pass Pass 0.8 PV6256/1579470 Binding MAPK10 (JNK3) LanthaScreen 48 49 49 1 Pass Pass 0.93 PV4563/1075329 Binding Km LYN A ZLYTE 48 48 48 0 Pass Pass 0.91 P2906/827663 Pass app KIT V559D T670I y LanthaScreen 46 49 47 3 Pass Pass 0.94 PV6316/1579472 Binding MET D1228H y LanthaScreen 46 48 47 2 Pass Pass 0.78 PV6208/1570985 Binding ABL1 Q252H y LanthaScreen 52 41 46 11 Pass Pass 0.76 PV6154/1570960 Binding AMPK (A1/B2/G1) LanthaScreen 49 43 46 5 Pass Pass 0.96 PV6244/1578463 Binding Km AMPK A2/B1/G1 ZLYTE 47 46 46 2 Pass Pass 0.93 PV4674/568101 Pass app BRAF LanthaScreen 44 47 46 2 Pass Pass 0.89 PV3848/1258788 Binding Km JAK2 JH1 JH2 ZLYTE 46 47 46 1 Pass Pass 0.81 PV4393/311662 Pass app Km NEK9 ZLYTE 46 45 46 1 Pass Pass 0.89 PV4653/38162 Pass app Km SYK ZLYTE 44 49 46 5 Pass Pass 0.85 PV3857/756818 Pass app AMPK (A2/B2/G2) LanthaScreen 44 45 45 1 Pass Pass 0.93 PV6250/1578465 Binding Km FLT3 ZLYTE 42 49 45 7 Pass Pass 0.78 PV3182/1012909 Pass app Km IKBKB (IKK beta) ZLYTE 52 39 45 13 Pass Pass 0.9 PV3836/1445179 Pass app Km SRC ZLYTE 45 44 45 1 Pass Pass 0.89 P3044/1255538 Pass app TNIK LanthaScreen 46 43 45 3 Pass Pass 0.8 PV6427/1578672 Binding Km RET ZLYTE 46 42 44 4 Pass Pass 0.89 PV3819/853376 Pass app TAOK1 LanthaScreen 45 43 44 2 Pass Pass 0.82 PV6415/1576240 Binding Km DAPK1 Adapta 42 43 43 2 Pass Pass 0.83 PV3969/32654 app Km PDGFRA (PDGFR ZLYTE 43 43 43 0 Pass Pass 0.82 PV3811/1269727 Pass app alpha) Km BLK ZLYTE 41 42 42 1 Pass Pass 0.8 PV3683/33635 Pass app CDK2/cyclin O LanthaScreen 39 42 41 4 Pass Pass 0.75 PV6286/1576891 Binding TEK (TIE2) y LanthaScreen 40 41 41 1 Pass Pass 0.92 PV6226/1570990 R849W Binding Km TYRO3 (RSE) ZLYTE 42 39 41 4 Pass Pass 0.9 PV3828/682475 Pass app Km ABL2 (Arg) ZLYTE 40 39 40 1 Pass Pass 0.92 PV3266/850069 Pass app AMPK (A1/B1/G2) LanthaScreen 40 40 40 0 Pass Pass 0.97 PV6238/1578461 Binding Km LCK ZLYTE 41 38 40 3 Pass Pass 0.79 P3043/850070 Pass app LIMK1 LanthaScreen 40 39 40 1 Pass Pass 0.87 PV4337/367810 Binding AMPK (A1/B1/G3) LanthaScreen 37 42 39 5 Pass Pass 0.92 PV6241/1578466 Binding Km MST1R (RON) ZLYTE 38 38 38 0 Pass Pass 0.83 PV4314/765277 Pass app Km PHKG1 ZLYTE 39 37 38 2 Pass Pass 0.75 PV3853/830447 Pass app Km CDK2/cyclin A ZLYTE 38 36 37 1 Pass Pass 0.88 PV3267/924344 Pass app DDR2 N456S y LanthaScreen 33 42 37 9 Pass Pass 0.86 PV6172/1570968 Binding Km RPS6KB1 ZLYTE 37 36 37 1 Pass Pass 0.84 PV3815/38944 Pass app (p70S6K) CDK2/cyclin A1 LanthaScreen 33 39 36 6 Pass Pass 0.89 PV6289/1576888 Binding Km PDGFRA T674I y ZLYTE 40 32 36 8 Pass Pass 0.67 PV3847/35891 Pass app ACVRL1 (ALK1) LanthaScreen 33 38 35 5 Pass Pass 0.79 PV4883/511550 Binding AMPK (A2/B2/G1) LanthaScreen 35 35 35 0 Pass Pass 0.94 PV6247/1578460 Binding FGFR3 K650M y LanthaScreen 33 38 35 5 Pass Pass 0.82 PV6187/1573650 Binding Km ITK ZLYTE 37 32 34 4 Pass Pass 0.71 PV3875/1430640 Pass app STK38L (NDR2) LanthaScreen 30 38 34 9 Pass Pass 0.54 PV6373/1575530 Binding Km CLK1 ZLYTE 33 34 33 0 Pass Pass 0.88 PV3315/943590 Pass app Km EPHB1 ZLYTE 34 31 33 3 Pass Pass 0.91 PV3786/34225 Pass app RET V804M y LanthaScreen 35 31 33 4 Pass Pass 0.82 PV6223/1570988 Binding TTK LanthaScreen 33 34 33 1 Pass Pass 0.77 PV3792/558743 Binding Km PDGFRB (PDGFR ZLYTE 34 30 32 4 Pass Pass 0.78 P3082/27567 Pass app beta) WEE1 LanthaScreen 28 36 32 7 Pass Pass 0.64 PV3817/784632 Binding Km CSNK2A2 (CK2 ZLYTE 32 30 31 2 Pass Pass 0.81 PV3624/32653 Pass app alpha 2) Km EGFR (ErbB1) y ZLYTE 34 29 31 4 Pass Pass 0.9 PV4879/1189155 Pass app T790M L858R Km MET (cMet) ZLYTE 30 33 31 4 Pass Pass 0.79 PV3143/625156 Pass app Km TXK ZLYTE 27 36 31 9 Pass Pass 0.86 PV5860/750657 Pass app Km MET M1250T y ZLYTE 26 34 30 8 Pass Pass 0.86 PV3968/34718 Pass app Km NEK2 ZLYTE 29 30 30 0 Pass Pass 0.81 PV3360/1086245 Pass app SLK LanthaScreen 29 32 30 4 Pass Pass 0.95 PV3830/34390 Binding Km ABL1 T315I y ZLYTE 30 29 29 1 Pass Pass 0.84 PV3866/39639 Pass app ACVR2B LanthaScreen 27 31 29 4 Pass Pass 0.86 PV6049/877066 Binding Km DYRK1A ZLYTE 30 27 28 4 Pass Pass 0.9 PV3785/683159 Pass app NLK LanthaScreen 26 29 28 3 Pass Pass 0.88 PV4309/35323 Binding Km ROS1 ZLYTE 30 26 28 4 Pass Pass 0.81 PV3814/479684 Pass app AXL R499C y LanthaScreen 28 27 27 1 Pass Pass 0.89 PV6253/1578673 Binding Km CHEK2 (CHK2) ZLYTE 27 27 27 0 Pass Pass 0.84 PV3367/1033750 Pass app Km EPHA1 ZLYTE 29 14 27 5 Pass Pass 0.85 PV3841/1138343 Pass app Km HCK ZLYTE 26 18 27 2 Pass Pass 0.87 PV6128/862448 Pass app Km SGK (SGK1) ZLYTE 28 26 27 2 Pass Pass 0.88 PV3818/1088196 Pass app CDK2/cyclin A2 LanthaScreen 24 29 26 5 Pass Pass 0.7 PV6292/1576892 Binding MAP3K11 (MLK3) LanthaScreen 24 29 26 5 Pass Pass 0.93 PV3788/869925 Binding MERTK (cMER) y LanthaScreen 24 27 26 3 Pass Pass 0.92 PV6325/1578675 A708S Binding Km PRKX ZLYTE 22 30 26 8 Pass Pass 0.87 PV3813/34283 Pass app Km DYRK3 ZLYTE 26 24 25 2 Pass Pass 0.89 PV3837/290370 Pass app Km EGFR (ErbB1) y ZLYTE 25 25 25 0 Pass Pass 0.85 PV4803/1123633 Pass app T790M 100 MAPK8 (JNK1) ZLYTE 33 18 25 15 Pass Pass 0.79 PV3319/1354818 Pass TNK2 (ACK) LanthaScreen 25 26 25 1 Pass Pass 0.92 PV4807/407338 Binding Km AXL ZLYTE 22 25 24 3 Pass Pass 0.86 PV3971/873922 Pass app LATS2 LanthaScreen 23 25 24 1 Pass Pass 0.91 PV6364/1575533 Binding Km MERTK (cMER) ZLYTE 27 22 24 5 Pass Pass 0.82 PV3627/32658 Pass app PRKACG (PRKAC LanthaScreen 28 19 24 9 Pass Pass 0.66 PV6391/1577047 gamma) Binding Km AURKC (Aurora ZLYTE 23 23 23 0 Pass Pass 0.66 PV3856/1078206 Pass app C) FGFR1 V561M y LanthaScreen 20 25 23 5 Pass Pass 0.91 PV6343/1578678 Binding Km MELK ZLYTE 25 22 23 3 Pass Pass 0.85 PV4823/819467 Pass app Km NEK4 ZLYTE 23 23 23 0 Pass Pass 0.88 PV4315/924342 Pass app ACVR2A LanthaScreen 23 21 22 2 Pass Pass 0.76 PV6124/862446 Binding ICK LanthaScreen 22 21 22 0 Pass Pass 0.86 PV6358/1577056 Binding MAP3K14 (NIK) LanthaScreen 20 24 22 3 Pass Pass 0.91 PV4902/1296958 Binding MAP3K7/MAP3K7 LanthaScreen 22 22 22 0 Pass Pass 0.89 PV4394/930475 IP1 (TAK1-TAB1) Binding Km GSK3A (GSK3 ZLYTE 20 22 21 2 Pass Pass 0.91 PV6126/862449 Pass app alpha) Km GSK3B (GSK3 ZLYTE 21 21 21 0 Pass Pass 0.79 PV3365/371501 Pass app beta) Km CDK9/cyclin T1 Adapta 18 22 20 4 Pass Pass 0.88 PV4131/1370615 app Km EPHA4 ZLYTE 18 21 20 2 Pass Pass 0.9 PV3651/32933 Pass app Km HIPK2 ZLYTE 21 19 20 2 Pass Pass 0.93 PV5275/452552 Pass app 100 MAPK10 (JNK3) ZLYTE 20 21 20 0 Pass Pass 0.9 PV4563/1075329 Pass Km CAMK2D ZLYTE 18 19 19 1 Pass Pass 0.91 PV3373/31647 Pass app (CaMKII delta) CAMK2G LanthaScreen 18 19 18 1 Pass Pass 0.77 PV6268/1576884 (CaMKII gamma) Binding FYN A LanthaScreen 16 21 18 6 Pass Pass 0.81 PV6346/1575529 Binding KIT D820E y LanthaScreen 18 19 18 2 Pass Pass 0.97 PV6307/1576885 Binding MAP4K3 (GLK) LanthaScreen 16 21 18 6 Pass Pass 0.87 PV6349/1579471 Binding MYO3B (MYO3 LanthaScreen 17 20 18 3 Pass Pass 0.95 PV6367/1577055 beta) Binding Km NTRK1 (TRKA) ZLYTE 16 20 18 3 Pass Pass 0.73 PV3144/1347534 Pass app Km NTRK3 (TRKC) ZLYTE 17 19 18 3 Pass Pass 0.85 PV3617/708766 Pass app RAF1 (cRAF) y LanthaScreen 15 20 18 4 Pass Pass 0.91 PV3805/1293604 Y340D Y341D Binding RET G691S y LanthaScreen 19 18 18 1 Pass Pass 0.8 PV6214/1570982 Binding BRSK2 LanthaScreen 16 17 17 1 Pass Pass 0.87 PV6259/1576239 Binding LIMK2 LanthaScreen 14 19 17 5 Pass Pass 0.95 PV3860/355434 Binding PRKACB (PRKAC LanthaScreen 16 18 17 2 Pass Pass 0.82 PV6388/1577048 beta) Binding Km CDK1/cyclin B ZLYTE 16 15 16 1 Pass Pass 0.85 PV3292/873341 Pass app CDK2/cyclin E1 LanthaScreen 15 17 16 2 Pass Pass 0.66 PV6295/1576887 Binding Km EPHB2 ZLYTE 14 17 16 3 Pass Pass 0.91 PV3625/1386867 Pass app Km HIPK4 ZLYTE 18 14 16 4 Pass Pass 0.89 PV3852/719847 Pass app 100 MAPK9 (JNK2) ZLYTE 12 21 16 9 Pass Pass 0.73 PV3620/32388 Pass Km PIK3CD/PIK3R1 Adapta 22 9 16 12 Pass Pass 0.88 PV5273/1147693 app (p110 delta/p85 alpha) Km RPS6KA6 (RSK4) ZLYTE 14 17 16 3 Pass Pass 0.63 PV4557/37496 Pass app Km CDK7/cyclin Adapta 17 14 15 2 Pass Pass 0.8 PV3868/1427412 app H/MNAT1 Km EPHB4 ZLYTE 15 14 15 2 Pass Pass 0.73 PV3251/29241 Pass app 100 MAP3K8 (COT) ZLYTE 19 11 15 7 Pass Pass 0.89 PV4313/1111069 Pass 100 PDK1 ZLYTE 14 16 15 1 Pass Pass 0.81 P3001/1394674 Pass Km RPS6KA2 (RSK3) ZLYTE 17 13 15 4 Pass Pass 0.89 PV3846/34468 Pass app TLK1 LanthaScreen 13 17 15 4 Pass Pass 0.88 PV6421/1576241 Binding EGFR (ErbB1) y LanthaScreen 14 13 14 1 Pass Pass 0.78 PV6178/1570967 d746-750 Binding EPHA6 LanthaScreen 9 20 14 11 Pass Pass 0.63 PV6337/1575527 Binding Km PRKG2 (PKG2) ZLYTE 16 13 14 3 Pass Pass 0.87 PV3973/273926 Pass app Km RPS6KA3 (RSK2) ZLYTE 17 10 14 7 Pass Pass 0.83 PV3323/1361669 Pass app Km TEK (Tie2) ZLYTE 11 17 14 6 Pass Pass 0.59 PV3628/34398 Pass app ALK F1174L y LanthaScreen 12 14 13 2 Pass Pass 0.91 PV6160/1570964 Binding Km HIPK3 (YAK1) ZLYTE 15 11 13 4 Pass Pass 0.92 PV4209/I076022 Pass app MAPK9 (JNK2) LanthaScreen 12 14 13 3 Pass Pass 0.91 PV3620/32388 Binding Km ROCK2 ZLYTE 12 14 13 2 Pass Pass 0.74 PV3759/843703 Pass app Km RPS6KA1 (RSK1) ZLYTE 15 11 13 4 Pass Pass 0.83 PV3680/880119 Pass app Km STK22B (TSSK2) ZLYTE 12 14 13 1 Pass Pass 0.79 PV3622/32396 Pass app Km BMX ZLYTE 12 13 12 1 Pass Pass 0.89 PV3371/953336 Pass app Km CAMK1D (CaMKI ZLYTE 12 13 12 1 Pass Pass 0.85 PV3663/1042984 Pass app delta) Km CSK ZLYTE 13 10 12 2 Pass Pass 0.88 P2927/1205898 Pass app Km FGFR2 ZLYTE 12 11 12 1 Pass Pass 0.93 PV3368/31517 Pass app Km FRK (PTK5) ZLYTE 11 13 12 2 Pass Pass 0.84 PV3874/34553 Pass app Km HIPK1 (Myak) ZLYTE 11 13 12 1 Pass Pass 0.89 PV4561/1126221 Pass app MAP3K3 LanthaScreen 10 13 12 3 Pass Pass 0.79 PV3876/702480 (MEKK3) Binding Km MAP4K5 (KHS1) ZLYTE 11 12 12 0 Pass Pass 0.65 PV3682/1383139 Pass app Km MUSK ZLYTE 15 8 12 7 Pass Pass 0.67 PV3834/1217900 Pass app RET M918T y LanthaScreen 10 13 12 3 Pass Pass 0.64 PV6217/1570989 Binding Km DYRK1B ZLYTE 14 9 11 5 Pass Pass 0.91 PV4649/877059 Pass app EPHA7 LanthaScreen 10 12 11 2 Pass Pass 0.62 PV3689/33790 Binding Km PLK1 ZLYTE 12 9 11 3 Pass Pass 0.89 PV3501/39441 Pass app Km CAMK2B ZLYTE 11 8 10 3 Pass Pass 0.81 PV4205/35330 Pass app (CaMKII beta) Km CDC42 BPB ZLYTE 6 13 10 7 Pass Pass 0.88 PV4399/36845 Pass app (MRCKB) CDK9 (Inactive) LanthaScreen 8 13 10 5 Pass Pass 0.93 PV6304/1579469 Binding CDK9/cyclin K LanthaScreen 11 9 10 2 Pass Pass 0.74 PV4335/35774 Binding Km CSNK2A1 (CK2 ZLYTE 13 7 10 7 Pass Pass 0.73 PV3248/1240448 Pass app alpha 1) Km JAK1 ZLYTE 11 10 10 2 Pass Pass 0.62 PV4774/1240449 Pass app MAP3K2 LanthaScreen 11 9 10 2 Pass Pass 0.75 PV3822/1171755 (MEKK2) Binding Km PRKCB2 (PKC ZLYTE 12 8 10 4 Pass Pass 0.82 P2251/930444 Pass app beta II) Km PRKCH (PKC eta) ZLYTE 12 8 10 4 Pass Pass 0.62 P2633/25587 Pass app Km ROCK1 ZLYTE 6 14 10 8 Pass Pass 0.78 PV3691/37178 Pass app Km SGK2 ZLYTE 7 12 10 5 Pass Pass 0.78 PV3858/1099019 Pass app STK39 (STLK3) LanthaScreen 10 9 10 1 Pass Pass 0.54 PV6412/1608283 Binding ALK C1156Y y LanthaScreen 7 12 9 5 Pass Pass 0.98 PV6157/1570963 Binding Km EGFR (ErbB1) ZLYTE 10 9 9 2 Pass Pass 0.89 PV3872/1004026 Pass app Km EPHA8 ZLYTE 11 7 9 4 Pass Pass 0.81 PV3844/36870 Pass app KIT V654A y LanthaScreen 7 10 9 3 Pass Pass 0.82 PV4132/35129 Binding 100 MAP2K6 (MKK6) ZLYTE 0 19 9 19 Pass Pass 0.85 PV3318/884909 Pass Km NEK6 ZLYTE 12 6 9 7 Pass Pass 0.76 PV3353/30778 Pass app Km PIK3CG (p110 Adapta 11 8 9 3 Pass Pass 0.92 PV4786/1153861 app gamma) CAMKK2 LanthaScreen 7 9 8 2 Pass Pass 0.93 PV4206/35319 (CaMKK beta) Binding CASK LanthaScreen 6 10 3 4 Pass Pass 0.75 PV6271/1576243 Binding Km FES (FPS) ZLYTE 9 7 8 2 Pass Pass 0.84 PV3354/35734 Pass app FGFR3 G697C y LanthaScreen 13 4 8 9 Pass Pass 0.74 PV6184/1570969 Binding Km FGFR3 K650E y ZLYTE 11 6 8 5 Pass Pass 0.85 PV4392/36445 Pass app MAP2K1 (MEK1) y LanthaScreen 10 7 8 2 Pass Pass 0.92 P3099/38541 S218D S222D Binding 100 MAP2K2 (MEK2) ZLYTE 13 2 8 10 Pass Pass 0.92 PV3615/32519 Pass Km MAPK13 (p38 ZLYTE 7 9 8 2 Pass Pass 0.83 PV3656/36817 Pass app delta) Km PAK1 ZLYTE 8 8 8 0 Pass Pass 0.86 PV3820/35463 Pass app ZAK LanthaScreen 6 10 8 4 Pass Pass 0.92 PV3882/34603 Binding 10 CAMK1 (CaMK1) Adapta 7 8 7 1 Pass Pass 0.86 PV4391/36046 CDK1/cyclin A2 LanthaScreen 2 12 7 11 Pass Pass 0.73 PV6280/1579468 Binding Km CLK2 ZLYTE 5 9 7 4 Pass Pass 0.81 PV4201/873335 Pass app Km DCAMKL2 ZLYTE 11 3 7 8 Pass Pass 0.63 PV4297/869931 Pass app (DCK2) Km FER ZLYTE 4 9 7 5 Pass Pass 0.71 PV3806/38946 Pass app Km FRAP1 (mTOR) ZLYTE 2 12 7 10 Pass Pass 0.8 PV4753/873345 Pass app MAP2K3 (MEK3) LanthaScreen 5 8 7 4 Pass Pass 0.61 PV3662/357368 Binding MAP3K5 (ASK1) LanthaScreen 7 8 7 1 Pass Pass 0.72 PV3809/666419 Binding Km PIM1 ZLYTE 11 3 7 9 Pass Pass 0.76 PV3503/811382 Pass app CDK3/cyclin E1 LanthaScreen 2 9 6 7 Pass Pass 0.62 PV6298/1579411 Binding Km EPHA2 ZLYTE 1 12 6 12 Pass Pass 0.77 PV3688/36904 Pass app Km ERBB4 (HER4) ZLYTE 8 5 6 4 Pass Pass 0.74 PV3626/32657 Pass app Km FLT1 (VEGFR1) ZLYTE 7 4 6 3 Pass Pass 0.81 PV3666/33924 Pass app Km IRAK4 ZLYTE 5 8 6 3 Pass Pass 0.78 PV3362/1088346 Pass app Km KIT T6701 y ZLYTE 6 7 6 2 Pass Pass 0.71 PV3869/34504 Pass app Km LTK (TYK1) ZLYTE 5 7 6 1 Pass Pass 0.78 PV4651/768522 Pass app Km MAPK1 (ERK2) ZLYTE 6 6 6 0 Pass Pass 0.86 PV3313/904347 Pass app Km MAPKAPK5 ZLYTE 6 7 6 1 Pass Pass 0.78 PV3301/880117 Pass app (PRAK) Km NTRK2 (TRKB) ZLYTE 5 7 6 1 Pass Pass 0.93 PV3616/35706 Pass app Km PAK6 ZLYTE 9 4 6 5 Pass Pass 0.8 PV3502/625425 Pass app Km PRKC1 (PKC iota) ZLYTE 5 7 6 2 Pass Pass 0.77 PV3183/28662 Pass app Km PTK2B (FAK2) ZLYTE 8 4 6 4 Pass Pass 0.8 PV4567/883370 Pass app TESK2 LanthaScreen 14 −3 6 16 Pass Pass 0.74 PV6418/1576242 Binding Km ADRBK1 (GRK2) ZLYTE 3 7 5 4 Pass Pass 0.88 PV3361/883372 Pass app Km ADRBK2 (GRK3) ZLYTE 6 4 5 2 Pass Pass 0.71 PV3827/38897 Pass app ALK L1196M y LanthaScreen 1 9 5 8 Pass Pass 0.92 PV6166/1570971 Binding Km BTK ZLYTE 3 6 5 3 Pass Pass 0.89 PV3363/1405298 Pass app Km CDK5/p35 ZLYTE 7 2 5 5 Pass Pass 0.89 PV3000/25348 Pass app Km EGFR (ErbB1) y ZLYTE 6 5 5 1 Pass Pass 0.89 PV3873/34562 Pass app L861Q Km FGFR3 ZLYTE 6 4 5 2 Pass Pass 0.84 PV3145/28459 Pass app GRK1 LanthaScreen 7 2 5 5 Pass Pass 0.96 PV6352/1577053 Binding 100 MAP2K1 (MEK1) ZLYTE 7 3 5 4 Pass Pass 0.82 PV3303/1081576 Pass MAP2K1 (MEK1) LanthaScreen 6 5 5 1 Pass Pass 0.95 PV3303/1081567 Binding MAP2K2 (MEK2) LanthaScreen 5 5 5 0 Pass Pass 0.94 PV3615/32519 Binding MAP2K6 (MKK6) y LanthaScreen 5 5 5 0 Pass Pass 0.91 PV3293/877061 S207E T211E Binding Km MAPK11 (p38 ZLYTE 6 4 5 2 Pass Pass 0.85 PV3679/1131827 Pass app beta) Km PAK3 ZLYTE 7 2 5 4 Pass Pass 0.86 PV3789/34118 Pass app Km PI4KB (PI4K beta) Adapta 7 3 5 4 Pass Pass 0.95 PV5277/943589 app Km STK3 (MST2) ZLYTE 5 6 5 1 Pass Pass 0.7 PV4805/371195 Pass app STK32B (YANK2) LanthaScreen 1 8 5 7 Pass Pass 0.9 PV6406/1577058 Binding Km TAOK2 (TAO1) ZLYTE 3 6 5 3 Pass Pass 0.8 PV3760/1011094 Pass app ALKR1275Q y LanthaScreen 0 7 4 7 Pass Pass 0.89 PV6169/1570970 Binding Km CDC42 BPA ZLYTE 4 4 4 0 Pass Pass 0.7 PV4398/1314130 Pass app (MRCKA) Km EGFR (ErbB1) y ZLYTE 6 3 4 3 Pass Pass 0.72 PV4128/279551 Pass app L858R EPHA3 LanthaScreen 6 3 4 4 Pass Pass 0.82 PV3359/673524 Binding Km GRK7 ZLYTE 3 5 4 2 Pass Pass 0.86 PV3823/34013 Pass app Km INSRR (IRR) ZLYTE 5 4 4 1 Pass Pass 0.91 PV3808/34272 Pass app 100 MAPK14 (p38 ZLYTE −1 9 4 10 Pass Pass 0.87 PV3304/1475037 Pass alpha) MYLK (MLCK) LanthaScreen 5 3 4 2 Pass Pass 0.91 PV4339/36152 Binding Km PRKCB1 (PKC ZLYTE 5 3 4 2 Pass Pass 0.71 P2291/299686 Pass app beta I) 100 RAF1 (cRAF) y ZLYTE 5 3 4 2 Pass Pass 0.91 PV3805/1293604 Pass Y340D Y341D Km RPS6KA5 (MSK1) ZLYTE 6 3 4 2 Pass Pass 0.84 PV3681/380935 Pass app Km SRMS (Srm) ZLYTE 5 3 4 2 Pass Pass 0.84 PV4214/1110226 Pass app Km ZAP70 ZLYTE 4 4 4 0 Pass Pass 0.86 P2782/843705 Pass app Km AKT2 (PKB beta) ZLYTE 3 2 3 1 Pass Pass 0.81 PV3184/28770 Pass app Km EPHA5 ZLYTE 3 4 3 1 Pass Pass 0.74 PV3840/34383 Pass app Km EPHB3 ZLYTE 3 3 3 0 Pass Pass 0.94 PV3658/33066 Pass app Km FGFR4 ZLYTE 7 −2 3 9 Pass Pass 0.65 P3054/26967 Pass app Km KIT ZLYTE 1 5 3 4 Pass Pass 0.76 P3081/1344384 Pass app Km MAPK12 (p38 ZLYTE 4 3 3 1 Pass Pass 0.87 PV3654/1140849 Pass app gamma) Km NEK7 ZLYTE 5 2 3 3 Pass Pass 0.81 PV3833/34387 Pass app Km PAK2 (PAK65) ZLYTE 6 −1 3 7 Pass Pass 0.87 PV4565/924347 Pass app Km PIM2 ZLYTE −1 7 3 7 Pass Pass 0.76 PV3649/32930 Pass app Km PRKACA (PKA) ZLYTE 4 1 3 3 Pass Pass 0.8 P2912/37377 Pass app Km PRKG1 ZLYTE 2 5 3 3 Pass Pass 0.9 PV4340/893283 Pass app Km SGKL (SGK3) ZLYTE 3 4 3 1 Pass Pass 0.87 PV3859/38954 Pass app Km AKT1 (PKB alpha) ZLYTE 1 3 2 2 Pass Pass 0.89 P2999/1159806 Pass app Km AKT3 (PKB ZLYTE 3 1 2 2 Pass Pass 0.88 PV3185/28771 Pass app gamma) Km CAMK2A ZLYTE 4 0 2 4 Pass Pass 0.89 PV3142/28192 Pass app (CaMKII alpha) Km CDK5/p25 ZLYTE 3 1 2 2 Pass Pass 0.79 PV4676/907645 Pass app Km CLK3 ZLYTE 1 3 2 1 Pass Pass 0.88 PV3826/939820 Pass app DDR1 LanthaScreen 3 2 2 1 Pass Pass 0.95 PV6047/693053 Binding Km GRK6 ZLYTE 2 2 2 1 Pass Pass 0.84 PV3661/37437 Pass app KIT T670E y LanthaScreen 2 2 2 1 Pass Pass 0.9 PV6313/1575536 Binding Km MAP4K2 (GCK) ZLYTE 6 −1 2 8 Pass Pass 0.88 PV4211/748356 Pass app Km MATK (HYL) ZLYTE 1 2 2 0 Pass Pass 0.83 PV3370/31553 Pass app Km MST4 ZLYTE 2 3 2 0 Pass Pass 0.76 PV3690/1205875 Pass app Km PASK ZLYTE 3 1 2 2 Pass Pass 0.68 PV3972/762487 Pass app Km STK23 (MSSK1) ZLYTE 2 1 2 1 Pass Pass 0.86 PV3880/1214750 Pass app TAOK3 (JIK) LanthaScreen 3 1 2 2 Pass Pass 0.86 PV3652/32935 Binding Km ALK ZLYTE 4 2 1 5 Pass Pass 0.86 PV3867/1542512 Pass app CDK8/cyclin C LanthaScreen 0 3 1 4 Pass Pass 0.94 PV4402/1177216 Binding Km CSNK1A1 (CK1 ZLYTE 2 1 1 1 Pass Pass 0.84 PV3850/1004025 Pass app alpha 1) Km CSNK1E (CK1 ZLYTE −2 4 1 6 Pass Pass 0.75 PV3500/866725 Pass app epsilon) Km CSNK1G3 (CK1 ZLYTE 4 −2 1 6 Pass Pass 0.85 PV3838/1140848 Pass app gamma 3) Km IGF1R ZLYTE 1 2 1 2 Pass Pass 0.78 PV3250/924345 Pass app MAP2K6 (MKK6) LanthaScreen −2 4 1 6 Pass Pass 0.86 PV3318/884909 Binding Km MAPK14 (p38 ZLYTE 2 1 1 1 Pass Pass 0.94 PV3304/1475037 Pass app alpha) Direct Km PTK2 (FAK) ZLYTE 0 2 1 2 Pass Pass 0.79 PV3832/1378055 Pass app Km RPS6KA4 (MSK2) ZLYTE 0 2 1 3 Pass Pass 0.84 PV3782/990109 Pass app Km STK24 (MST3) ZLYTE −5 8 1 14 Pass Pass 0.7 PV3650/32932 Pass app TEC LanthaScreen 0 2 1 2 Pass Pass 0.93 PV3269/910411 Binding WNK2 LanthaScreen −4 5 1 9 Pass Pass 0.86 PV4341/35976 Binding CAMKK1 LanthaScreen 2 −1 0 2 Pass Pass 0.8 PV4670/406782 (CAMKKA) Binding DDR2 LanthaScreen 0 1 0 2 Pass Pass 0.94 PV3870/916220 Binding Km INSR ZLYTE −1 1 0 3 Pass Pass 0.81 PV3781/1314127 Pass app Km MAPK3 (ERK1) ZLYTE 3 −2 0 5 Pass Pass 0.86 PV3311/1255534 Pass app Km MAPKAPK2 ZLYTE 0 −1 0 1 Pass Pass 0.82 PV33I7/36559 Pass app 10 PI4KA (PI4K Adapta 3 −3 0 6 Pass Pass 0.81 PV5689/1131829 alpha) Km PRKCD (PKC ZLYTE 4 −4 0 8 Pass Pass 0.73 P2293/39038 Pass app delta) RIPK3 LanthaScreen −1 1 0 2 Pass Pass 0.84 PV6397/1610742 Binding Km SPHK1 Adapta 10 −9 0 19 Pass Pass 0.77 PV5214/933639 app Km STK4 (MST1) ZLYTE 0 0 0 0 Pass Pass 0.73 PV3854/38395 Pass app CDK5 (Inactive) LanthaScreen 1 −2 −1 3 Pass Pass 0.68 PV6301/1576893 Binding Km DNA-PK ZLYTE 2 −4 −1 7 Pass Pass 0.69 PV5864/1594760 Pass app Km DYRK4 ZLYTE −2 0 −1 1 Pass Pass 0.82 PV3871/37361 Pass app Km EEF2K ZLYTE −1 0 −1 1 Pass Pass 0.87 PV4559/1075327 Pass app Km ERBB2 (HER2) ZLYTE 0 −3 −1 3 Pass Pass 0.74 PV3366/1185123 Pass app Km PTK6 (Brk) ZLYTE −1 −1 −1 0 Pass Pass 0.86 PV3291/1205876 Pass app STK32C (YANK3) LanthaScreen −4 3 −1 6 Pass Pass 0.68 PV6409/1577045 Binding Km CAMK4 ZLYTE −2 −2 −2 0 Pass Pass 0.84 PV3310/1103512 Pass app (CaMKIV) LATS1 LanthaScreen −5 1 −2 6 Pass Pass 0.62 PV6361/1575532 Binding 10 PIK3C2B (PI3K- Adapta 3 −7 −2 9 Pass Pass 0.87 PV5374/1223244 C2 beta) Km PRKCA (PKC ZLYTE 0 −5 −2 6 Pass Pass 0.71 P2232/38479 Pass app alpha) Km SRPK1 ZLYTE −1 −2 −2 2 Pass Pass 0.94 PV4215/1182336 Pass app Km STK25 (YSK1) ZLYTE 0 −4 −2 4 Pass Pass 0.8 PV3657/33163 Pass app WNK3 LanthaScreen −3 0 −2 2 Pass Pass 0.83 PV4342/36047 Binding Km CSNK1D (CK1 ZLYTE −1 −5 −3 5 Pass Pass 0.83 PV3665/843704 Pass app delta) Km FGFR1 ZLYTE −5 −2 −3 3 Pass Pass 0.8 PV3146/28427 Pass app Km GRK5 ZLYTE 5 −10 −3 15 Pass Pass 0.82 PV3824/879275 Pass app Km MAPKAPK3 ZLYTE 1 −8 −3 9 Pass Pass 0.86 PV3299/38895 Pass app Km PRKCE (PKC ZLYTE 1 −6 −3 8 Pass Pass 0.83 P2292/37717 Pass app epsilon) Km SRPK2 ZLYTE −2 −4 −3 2 Pass Pass 0.91 PV3829/900365 Pass app CDK11 (Inactive) LanthaScreen −1 −7 −4 7 Pass Pass 0.71 PV6283/1576889 Binding Km GRK4 ZLYTE −4 −5 −5 1 Pass Pass 0.86 PV3807/618977 Pass app Km PIK3CA/PIK3R1 Adapta −5 −4 −5 1 Pass Pass 0.79 PV4788/616250 app (p110 alpha/p85 alpha) Km PKN1 (PRK1) ZLYTE −6 −4 −5 2 Pass Pass 0.68 PV3790/356552 Pass app Km PRKCG (PKC ZLYTE −9 −1 −5 8 Pass Pass 0.73 P2233/39126 Pass app gamma) Km CSNK1G1 (CK1 ZLYTE −14 2 −6 16 Pass Pass 0.77 PV3825/34360 Pass app gamma 1) Km GSG2 (Haspin) Adapta 7 −20 −6 26 Pass Pass 0.71 PV5708/869949 app Km ACVR1B (ALK4) ZLYTE −10 −4 −7 6 Pass Pass 0.9 PV4312/919690 Pass app Km PIK3C3 (hVPS34) Adapta −5 −9 −7 4 Pass Pass 0.91 PV5126/853378 app Km PIK3C2A (PI3K- Adapta −7 −9 −8 2 Pass Pass 0.88 PV5586/1123632 app C2 alpha) 10 SPHK2 Adapta −16 −2 −9 14 Pass Pass 0.56 PV5216/1296957 Km CSNK1G2 (CK1 ZLYTE −7 −16 −11 9 Pass Pass 0.79 PV3499/1120155 Pass app gamma 2) Km PRKCQ (PKC ZLYTE −6 −17 −12 11 Pass Pass 0.76 P2996/26231 Pass app theta) 100 BRAF ZLYTE −18 −10 −14 8 Pass Pass 0.83 PV3848/1258788 Pass Km PRKCZ (PKC zeta) ZLYTE −18 −16 −17 2 Pass Pass 0.7 P2273/31602 Pass app

TABLE S5-2 fold selectivity fold selectivity Technology ATP IC50 (nM) Hillslope R2 (TBK1) (IKBKE) ZLYTE Km app 1.04 1.12 0.9966 1.0 0.2 LanthaScreen 2.71 0.8 0.9917 2.6 0.5 Binding LanthaScreen 4.35 1.27 0.9998 4.2 0.8 Binding ZLYTE Km app 5.59 1.06 0.9955 5.4 1.0 ZLYTE Km app 14.2 0.55 0.9914 13.7 2.5 LanthaScreen 14.8 1.25 0.9989 14.2 2.6 Binding LanthaScreen 30.9 0.84 0.9797 29.7 5.5 Binding LanthaScreen 31.5 0.88 0.9956 30.3 5.6 Binding Adapta Km app 34.9 0.99 0.9945 33.6 6.2 ZLYTE Km app 35.1 1 0.9994 33.8 6.3 ZLYTE Km app 35.8 1.11 0.9993 34.4 6.4 ZLYTE Km app 41.5 1.49 0.9978 39.9 7.4 ZLYTE Km app 45.6 1.01 0.9981 43.8 8.2 ZLYTE Km app 47.7 0.84 0.9995 45.9 8.5 ZLYTE Km app 55 0.96 0.9993 52.9 9.8 ZLYTE Km app 59 0.69 0.9971 56.7 10.6 LanthaScreen 74.1 1 0.9972 71.3 13.3 Binding LanthaScreen 78.7 0.86 0.9971 75.7 14.1 Binding Adapta Km app 80.6 1 0.9983 77.5 14.4 ZLYTE Km app 81.3 1.12 0.9991 78.2 14.5 LanthaScreen 81.6 1.42 0.9789 78.5 14.6 Binding ZLYTE Km app 90.9 1.11 0.9974 87.4 16.3 LanthaScreen 104 1.22 0.997 100.0 18.6 Binding LanthaScreen 156 0.95 0.9986 150.0 27.9 Binding

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EQUIVALENTS AND SCOPE

While several inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/ac used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.

All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.

All references, patents, and patent applications disclosed herein are incorporated by reference with respect to the subject matter for which each is cited, which in some cases may encompass the entirety of the document.

The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”

The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.

As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of” or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03. It should be appreciated that embodiments described in this document using an open-ended transitional phrase (e.g., “comprising”) are also contemplated, in alternative embodiments, as “consisting of” and “consisting essentially of” the feature described by the open-ended transitional phrase. For example, if the disclosure describes “a composition comprising A and B,” the disclosure also contemplates the alternative embodiments “a composition consisting of A and B” and “a composition consisting essentially of A and B.” 

What is claimed is:
 1. A method for evaluating primary patient-derived tumor cell spheroids in a three-dimensional microfluidic device, the method comprising: obtaining primary patient-derived tumor cell spheroids from an enzyme treated tumor sample, suspending a first aliquot of the primary patient-derived tumor cell spheroids in a biocompatible gel, suspending a second aliquot of the primary patient-derived tumor cell spheroids in a biocompatible gel, placing the first aliquot of the primary patient-derived tumor cell spheroids in the biocompatible gel in a first three-dimensional microfluidic device, contacting the first aliquot with a first fluorophore dye selective for dead cells, the first fluorophore dye emitting fluorescence at a first wavelength when bound to a dead cell, contacting the first aliquot with a second fluorophore dye selective for live cells, the second fluorophore dye emitting fluorescence at a second wavelength different from the first wavelength when bound to a live cell, quantitating total fluorescence emitted by each of the first and second fluorophore dyes in primary patient-derived tumor cell spheroids in the first aliquot within the first three-dimensional microfluidic device, placing the second aliquot of the primary patient-derived tumor cell spheroid in the biocompatible gel in a second three-dimensional microfluidic device, contacting the second aliquot with the first fluorophore dye, contacting the second aliquot with the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye, quantitating total fluorescence emitted by each of the first and second fluorophore dyes in primary patient-derived tumor cell spheroids in the second aliquot within the second three-dimensional microfluidic device, and assessing a ratio of live to dead cells in each aliquot based on the total fluorescence quantitated in each three-dimensional microfluidic device.
 2. The method of claim 1, further comprising: culturing the second aliquot of the primary patient-derived tumor cell spheroids in the second three-dimensional microfluidic device in the presence of a first test compound; isolating RNA from the first aliquot and second aliquot of primary patient-derived tumor cell spheroids after total fluorescence emitted is measured; and analyzing gene expression of the first aliquot and second aliquot of primary patient-derived tumor cell spheroids based on the isolated RNA.
 3. The method of claim 2, wherein the second aliquot is cultured in the presence of the first test compound and a second test compound during the culturing step.
 4. The method of claim 3, wherein the second aliquot is further cultured in the presence of a third and/or fourth test compound during the culturing step.
 5. The method of claim 3, wherein the first and/or second test compound is a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof.
 6. The method of claim 3, wherein the first test compound is an immune checkpoint inhibitor and the second test compound is a small molecule compound.
 7. The method of claim 6, wherein the small molecule compound is a TBK-1 inhibitor.
 8. The method of claim 3, wherein the first and/or second test compound is a chemical from a test compound library.
 9. The method of claim 3, wherein the first test compound is an immune checkpoint inhibitor and the second test compound is a chemical from a test compound library.
 10. The method of claim 2, further comprising: culturing a third aliquot of the primary patient-derived tumor cell spheroids in a third three-dimensional microfluidic device in the presence of the first test compound and a second test compound; isolating RNA from the third aliquot of primary patient-derived tumor cell spheroids; and analyzing gene expression of the third aliquot of primary patient-derived tumor cell spheroids based on the isolated RNA.
 11. The method of claim 10, wherein the third aliquot is further cultured in the presence of a third and/or fourth test compound during the step of culturing the third aliquot.
 12. The method of claim 2, wherein the RNA is isolated from the supernatant or from the cell culture of the first aliquot and second aliquot of the primary patient-derived tumor cell spheroids.
 13. The method of claim 2, wherein the gene expression of the first aliquot and second aliquot of the primary patient-derived tumor cell spheroids is analyzed by performing RNA sequencing (RNA-seq) on the isolated RNA.
 14. The method of claim 2, wherein the primary patient-derived tumor cell spheroids are from an enzyme treated tumor sample derived from a patient.
 15. The method of claim 2, wherein the first test compound is an immune modulator.
 16. The method of claim 15, wherein the immune modulator comprises immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of CTLA-4, PD-1, PD-L1, TIM3, LAGS, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GALS, A2aR, and VISTA.
 17. The method of claim 16, wherein the immune checkpoint inhibitor inhibits PD-1.
 18. The method of claim 2, wherein the first and/or second aliquots are further cultured in the biocompatible gel.
 19. The method of claim 18, wherein the first and/or second aliquots are suspended in the biocompatible gel in a fluid channel of the three-dimensional microfluidic device before culturing. 